Overview

Dataset statistics

Number of variables293
Number of observations69359
Missing cells13249265
Missing cells (%)65.2%
Total size in memory153.7 MiB
Average record size in memory2.3 KiB

Variable types

Numeric222
Categorical60
Boolean3
Unsupported8

Alerts

4-fibf_1 has constant value "1.0" Constant
acetyl_1 has constant value "1.0" Constant
acetyl_2 has constant value "1.0" Constant
acetylsalicylic_1 has constant value "1.0" Constant
alcohol_1 has constant value "1.0" Constant
alcohol_2 has constant value "1.0" Constant
alprazolam_1 has constant value "1.0" Constant
alprazolam_2 has constant value "1.0" Constant
amphetamine_1 has constant value "1.0" Constant
amphetamine_2 has constant value "1.0" Constant
anpp_1 has constant value "1.0" Constant
aspirin_1 has constant value "1.0" Constant
aspirin_2 has constant value "1.0" Constant
barbiturates_1 has constant value "1.0" Constant
benzo_tag has constant value "1.0" Constant
benzodiazepine_1 has constant value "1.0" Constant
benzodiazepine_2 has constant value "1.0" Constant
buprenorphine_1 has constant value "1.0" Constant
buprenorphine_2 has constant value "1.0" Constant
butonitazene_1 has constant value "1.0" Constant
butyryl_1 has constant value "1.0" Constant
cannabis_1 has constant value "1.0" Constant
cannabis_tag has constant value "1.0" Constant
carfentanil_1 has constant value "1.0" Constant
carisoprodol_1 has constant value "1.0" Constant
chlordiazepoxide_1 has constant value "1.0" Constant
clonazepam_1 has constant value "1.0" Constant
clonazepam_2 has constant value "1.0" Constant
cocaine_1 has constant value "1.0" Constant
cocaine_2 has constant value "1.0" Constant
codeine_1 has constant value "1.0" Constant
codeine_2 has constant value "1.0" Constant
corona_1 has constant value "1.0" Constant
corona_2 has constant value "1.0" Constant
coronavirus_1 has constant value "1.0" Constant
coronavirus_2 has constant value "1.0" Constant
covid-19_1 has constant value "1.0" Constant
covid-19_2 has constant value "1.0" Constant
covid_tag has constant value "1.0" Constant
cyclobenzaprine_1 has constant value "1.0" Constant
cyclobenzaprine_2 has constant value "1.0" Constant
cyclopropyl_1 has constant value "1.0" Constant
despropionyl_1 has constant value "1.0" Constant
despropionyl_2 has constant value "1.0" Constant
dextromethorphan_1 has constant value "1.0" Constant
dextromethorphan_2 has constant value "1.0" Constant
dextrorphan_1 has constant value "1.0" Constant
diazepam_1 has constant value "1.0" Constant
diazepam_2 has constant value "1.0" Constant
dihydrocodeine_1 has constant value "1.0" Constant
drug_tag has constant value "1.0" Constant
estazolam_1 has constant value "1.0" Constant
eth_alc_tag has constant value "1.0" Constant
ethanol_1 has constant value "1.0" Constant
ethanol_2 has constant value "1.0" Constant
fen_analog_tag has constant value "1.0" Constant
fentanyl_1 has constant value "1.0" Constant
fentanyl_2 has constant value "1.0" Constant
fentanyl_tag has constant value "1.0" Constant
fibf_1 has constant value "1.0" Constant
flunitazene_1 has constant value "1.0" Constant
flurazepam_1 has constant value "1.0" Constant
furanyl_1 has constant value "1.0" Constant
furanyl_2 has constant value "1.0" Constant
hallucinogen_tag has constant value "1.0" Constant
heroin_1 has constant value "1.0" Constant
heroin_2 has constant value "1.0" Constant
hydrocodol_1 has constant value "1.0" Constant
hydrocodone_1 has constant value "1.0" Constant
hydrocodone_2 has constant value "1.0" Constant
hydromorphone_1 has constant value "1.0" Constant
hydromorphone_2 has constant value "1.0" Constant
hypoxia_tag has constant value "1.0" Constant
hypoxic_1 has constant value "1.0" Constant
hypoxic_2 has constant value "1.0" Constant
inhalant_1 has constant value "1.0" Constant
inhalant_tag has constant value "1.0" Constant
ischemic_1 has constant value "1.0" Constant
ischemic_2 has constant value "1.0" Constant
isotonitazene_1 has constant value "1.0" Constant
ketamine_1 has constant value "1.0" Constant
ketamine_2 has constant value "1.0" Constant
levorphanol_1 has constant value "1.0" Constant
lorazepam_1 has constant value "1.0" Constant
lorazepam_2 has constant value "1.0" Constant
lsd_1 has constant value "1.0" Constant
lsd_2 has constant value "1.0" Constant
lysergic_1 has constant value "1.0" Constant
lysergic_2 has constant value "1.0" Constant
mda_1 has constant value "1.0" Constant
mdma_1 has constant value "1.0" Constant
mdma_2 has constant value "1.0" Constant
meperidine_1 has constant value "1.0" Constant
metaxalone_1 has constant value "1.0" Constant
methadone_1 has constant value "1.0" Constant
methadone_2 has constant value "1.0" Constant
methamphetamine_1 has constant value "1.0" Constant
methamphetamine_2 has constant value "1.0" Constant
methocarbamol_1 has constant value "1.0" Constant
methorphan_1 has constant value "1.0" Constant
methorphan_2 has constant value "1.0" Constant
methoxyacetyl_1 has constant value "1.0" Constant
methylenedioxymethamphetamine_1 has constant value "1.0" Constant
methylenedioxymethamphetamine_2 has constant value "1.0" Constant
methylphenidate_1 has constant value "1.0" Constant
metonitazene_1 has constant value "1.0" Constant
mitragynine_1 has constant value "1.0" Constant
mitragynine_2 has constant value "1.0" Constant
morphine_1 has constant value "1.0" Constant
morphine_2 has constant value "1.0" Constant
nitazene_tag has constant value "1.0" Constant
nonfentanyl_opioid_tag has constant value "1.0" Constant
norfentanyl_1 has constant value "1.0" Constant
opiate_1 has constant value "1.0" Constant
opiate_2 has constant value "1.0" Constant
opiate_tag has constant value "1.0" Constant
opioid_1 has constant value "1.0" Constant
opioid_2 has constant value "1.0" Constant
oxazepam_1 has constant value "1.0" Constant
oxycodone_1 has constant value "1.0" Constant
oxycodone_2 has constant value "1.0" Constant
oxymorphone_1 has constant value "1.0" Constant
oxymorphone_2 has constant value "1.0" Constant
para-fluorobutyryl_1 has constant value "1.0" Constant
pcp_1 has constant value "1.0" Constant
pcp_2 has constant value "1.0" Constant
phencyclidine_1 has constant value "1.0" Constant
phencyclidine_2 has constant value "1.0" Constant
phentermine_1 has constant value "1.0" Constant
polysubstance_1 has constant value "1.0" Constant
polysubstance_2 has constant value "1.0" Constant
polysubstance_tag has constant value "1.0" Constant
propoxyphene_1 has constant value "1.0" Constant
sedative_tag has constant value "1.0" Constant
stimulant_tag has constant value "1.0" Constant
tarpentadol_1 has constant value "1.0" Constant
temazepam_1 has constant value "1.0" Constant
tizanidine_1 has constant value "1.0" Constant
topiramate_1 has constant value "1.0" Constant
topiramate_2 has constant value "1.0" Constant
toxic_tag has constant value "1.0" Constant
tramadol_1 has constant value "1.0" Constant
tramadol_2 has constant value "1.0" Constant
u-47700_1 has constant value "1.0" Constant
u-49900_1 has constant value "1.0" Constant
utonitazene_1 has constant value "1.0" Constant
valeryl_1 has constant value "1.0" Constant
xylazine_1 has constant value "1.0" Constant
xylazine_2 has constant value "1.0" Constant
CFTYPE has constant value "Park" Constant
CFSUBTYPE has constant value "Park" Constant
STATEFP_left has constant value "17.0" Constant
STATEFP_right has constant value "17.0" Constant
MTFCC has constant value "G5020" Constant
FUNCSTAT has constant value "S" Constant
PLATTED has constant value "O" Constant
hot has constant value "1" Constant
cold has constant value "1" Constant
__id has a high cardinality: 69359 distinct values High cardinality
casenumber has a high cardinality: 69359 distinct values High cardinality
chi_commarea has a high cardinality: 77 distinct values High cardinality
death_date has a high cardinality: 2970 distinct values High cardinality
geocoded_matched_address has a high cardinality: 5386 distinct values High cardinality
incident_city has a high cardinality: 429 distinct values High cardinality
incident_date has a high cardinality: 59289 distinct values High cardinality
incident_street has a high cardinality: 65442 distinct values High cardinality
location has a high cardinality: 48260 distinct values High cardinality
primary_cod has a high cardinality: 13692 distinct values High cardinality
primarycause has a high cardinality: 9901 distinct values High cardinality
primarycause_linea has a high cardinality: 2771 distinct values High cardinality
primarycause_lineb has a high cardinality: 399 distinct values High cardinality
residence_city has a high cardinality: 1211 distinct values High cardinality
secondarycause has a high cardinality: 10995 distinct values High cardinality
geometry has a high cardinality: 53589 distinct values High cardinality
AGENCY_DESC has a high cardinality: 155 distinct values High cardinality
MUNICIPALITY has a high cardinality: 130 distinct values High cardinality
GlobalID has a high cardinality: 156 distinct values High cardinality
pri_neigh has a high cardinality: 98 distinct values High cardinality
sec_neigh has a high cardinality: 78 distinct values High cardinality
CFNAME has a high cardinality: 86 distinct values High cardinality
ADDRESS has a high cardinality: 74 distinct values High cardinality
AFFGEOID has a high cardinality: 71 distinct values High cardinality
NAME_left has a high cardinality: 71 distinct values High cardinality
NAMELSAD has a high cardinality: 1697 distinct values High cardinality
GEOG has a high cardinality: 67 distinct values High cardinality
landuse_name has a high cardinality: 55 distinct values High cardinality
death_street has a high cardinality: 40373 distinct values High cardinality
death_city has a high cardinality: 297 distinct values High cardinality
death_location has a high cardinality: 5890 distinct values High cardinality
death_location_1 has a high cardinality: 152 distinct values High cardinality
death_datetime has a high cardinality: 68006 distinct values High cardinality
death_time has a high cardinality: 1440 distinct values High cardinality
4-fibf_1 has 69358 (> 99.9%) missing values Missing
acetyl_1 has 68335 (98.5%) missing values Missing
acetyl_2 has 69350 (> 99.9%) missing values Missing
acetylsalicylic_1 has 69357 (> 99.9%) missing values Missing
alcohol_1 has 69043 (99.5%) missing values Missing
alcohol_2 has 69288 (99.9%) missing values Missing
alprazolam_1 has 68331 (98.5%) missing values Missing
alprazolam_2 has 69345 (> 99.9%) missing values Missing
amphetamine_1 has 69153 (99.7%) missing values Missing
amphetamine_2 has 69344 (> 99.9%) missing values Missing
anpp_1 has 69357 (> 99.9%) missing values Missing
aspirin_1 has 69358 (> 99.9%) missing values Missing
aspirin_2 has 69356 (> 99.9%) missing values Missing
average_distance has 35722 (51.5%) missing values Missing
barbiturates_1 has 69355 (> 99.9%) missing values Missing
benzo_tag has 67453 (97.3%) missing values Missing
benzodiazepine_1 has 69143 (99.7%) missing values Missing
benzodiazepine_2 has 69349 (> 99.9%) missing values Missing
buprenorphine_1 has 69277 (99.9%) missing values Missing
buprenorphine_2 has 69358 (> 99.9%) missing values Missing
butonitazene_1 has 69358 (> 99.9%) missing values Missing
butyryl_1 has 69357 (> 99.9%) missing values Missing
cannabis_1 has 69358 (> 99.9%) missing values Missing
cannabis_tag has 69358 (> 99.9%) missing values Missing
carfentanil_1 has 69313 (99.9%) missing values Missing
carisoprodol_1 has 69343 (> 99.9%) missing values Missing
chi_commarea has 31017 (44.7%) missing values Missing
chi_ward has 31020 (44.7%) missing values Missing
chlordiazepoxide_1 has 69335 (> 99.9%) missing values Missing
clonazepam_1 has 68931 (99.4%) missing values Missing
clonazepam_2 has 69352 (> 99.9%) missing values Missing
closest_medical_center_km has 2086 (3.0%) missing values Missing
closest_pharmacy_km has 2086 (3.0%) missing values Missing
cocaine_1 has 65082 (93.8%) missing values Missing
cocaine_2 has 68830 (99.2%) missing values Missing
codeine_1 has 69298 (99.9%) missing values Missing
codeine_2 has 69355 (> 99.9%) missing values Missing
commissioner_district has 8907 (12.8%) missing values Missing
corona_1 has 54938 (79.2%) missing values Missing
corona_2 has 68445 (98.7%) missing values Missing
coronavirus_1 has 69331 (> 99.9%) missing values Missing
coronavirus_2 has 69354 (> 99.9%) missing values Missing
covid-19_1 has 54914 (79.2%) missing values Missing
covid-19_2 has 68454 (98.7%) missing values Missing
covid_related has 760 (1.1%) missing values Missing
covid_tag has 53989 (77.8%) missing values Missing
cyclobenzaprine_1 has 69205 (99.8%) missing values Missing
cyclobenzaprine_2 has 69358 (> 99.9%) missing values Missing
cyclopropyl_1 has 69236 (99.8%) missing values Missing
despropionyl_1 has 65484 (94.4%) missing values Missing
despropionyl_2 has 69335 (> 99.9%) missing values Missing
dextromethorphan_1 has 69332 (> 99.9%) missing values Missing
dextromethorphan_2 has 69358 (> 99.9%) missing values Missing
dextrorphan_1 has 69358 (> 99.9%) missing values Missing
diazepam_1 has 69114 (99.6%) missing values Missing
diazepam_2 has 69358 (> 99.9%) missing values Missing
dihydrocodeine_1 has 69344 (> 99.9%) missing values Missing
drug_tag has 56849 (82.0%) missing values Missing
estazolam_1 has 69357 (> 99.9%) missing values Missing
eth_alc_tag has 65660 (94.7%) missing values Missing
ethanol_1 has 66293 (95.6%) missing values Missing
ethanol_2 has 69107 (99.6%) missing values Missing
fen_analog_tag has 64587 (93.1%) missing values Missing
fentanyl_1 has 62223 (89.7%) missing values Missing
fentanyl_2 has 69279 (99.9%) missing values Missing
fentanyl_tag has 62120 (89.6%) missing values Missing
fibf_1 has 69356 (> 99.9%) missing values Missing
flunitazene_1 has 69357 (> 99.9%) missing values Missing
flurazepam_1 has 69354 (> 99.9%) missing values Missing
furanyl_1 has 69149 (99.7%) missing values Missing
furanyl_2 has 69358 (> 99.9%) missing values Missing
geocoded_latitude has 62547 (90.2%) missing values Missing
geocoded_longitude has 62547 (90.2%) missing values Missing
geocoded_matched_address has 62547 (90.2%) missing values Missing
geocoded_score has 62547 (90.2%) missing values Missing
gunrelated has 1252 (1.8%) missing values Missing
hallucinogen_tag has 68918 (99.4%) missing values Missing
heroin_1 has 64553 (93.1%) missing values Missing
heroin_2 has 69274 (99.9%) missing values Missing
hydrocodol_1 has 69358 (> 99.9%) missing values Missing
hydrocodone_1 has 68940 (99.4%) missing values Missing
hydrocodone_2 has 69351 (> 99.9%) missing values Missing
hydromorphone_1 has 69257 (99.9%) missing values Missing
hydromorphone_2 has 69358 (> 99.9%) missing values Missing
hypoxia_tag has 67225 (96.9%) missing values Missing
hypoxic_1 has 67324 (97.1%) missing values Missing
hypoxic_2 has 69353 (> 99.9%) missing values Missing
incident_city has 1669 (2.4%) missing values Missing
incident_date has 1658 (2.4%) missing values Missing
incident_street has 991 (1.4%) missing values Missing
incident_zip has 1640 (2.4%) missing values Missing
inhalant_1 has 69357 (> 99.9%) missing values Missing
inhalant_tag has 69357 (> 99.9%) missing values Missing
ischemic_1 has 69316 (99.9%) missing values Missing
ischemic_2 has 69298 (99.9%) missing values Missing
isotonitazene_1 has 69313 (99.9%) missing values Missing
ketamine_1 has 69342 (> 99.9%) missing values Missing
ketamine_2 has 69357 (> 99.9%) missing values Missing
latitude has 8898 (12.8%) missing values Missing
levorphanol_1 has 69358 (> 99.9%) missing values Missing
location has 8898 (12.8%) missing values Missing
location_address has 69359 (100.0%) missing values Missing
location_city has 69359 (100.0%) missing values Missing
location_state has 69359 (100.0%) missing values Missing
location_zip has 69359 (100.0%) missing values Missing
longitude has 8898 (12.8%) missing values Missing
lorazepam_1 has 69213 (99.8%) missing values Missing
lorazepam_2 has 69358 (> 99.9%) missing values Missing
lsd_1 has 69354 (> 99.9%) missing values Missing
lsd_2 has 69358 (> 99.9%) missing values Missing
lysergic_1 has 69353 (> 99.9%) missing values Missing
lysergic_2 has 69358 (> 99.9%) missing values Missing
mda_1 has 69344 (> 99.9%) missing values Missing
mdma_1 has 69274 (99.9%) missing values Missing
mdma_2 has 69356 (> 99.9%) missing values Missing
meperidine_1 has 69358 (> 99.9%) missing values Missing
metaxalone_1 has 69356 (> 99.9%) missing values Missing
methadone_1 has 68629 (98.9%) missing values Missing
methadone_2 has 69332 (> 99.9%) missing values Missing
methamphetamine_1 has 69030 (99.5%) missing values Missing
methamphetamine_2 has 69334 (> 99.9%) missing values Missing
methocarbamol_1 has 69352 (> 99.9%) missing values Missing
methorphan_1 has 69347 (> 99.9%) missing values Missing
methorphan_2 has 69358 (> 99.9%) missing values Missing
methoxyacetyl_1 has 69332 (> 99.9%) missing values Missing
methylenedioxymethamphetamine_1 has 69240 (99.8%) missing values Missing
methylenedioxymethamphetamine_2 has 69353 (> 99.9%) missing values Missing
methylphenidate_1 has 69354 (> 99.9%) missing values Missing
metonitazene_1 has 69281 (99.9%) missing values Missing
mitragynine_1 has 69249 (99.8%) missing values Missing
mitragynine_2 has 69357 (> 99.9%) missing values Missing
morphine_1 has 69167 (99.7%) missing values Missing
morphine_2 has 69353 (> 99.9%) missing values Missing
nitazene_tag has 69236 (99.8%) missing values Missing
nonfentanyl_opioid_tag has 62554 (90.2%) missing values Missing
norfentanyl_1 has 69337 (> 99.9%) missing values Missing
opiate_1 has 69083 (99.6%) missing values Missing
opiate_2 has 69341 (> 99.9%) missing values Missing
opiate_tag has 59194 (85.3%) missing values Missing
opioid_1 has 68952 (99.4%) missing values Missing
opioid_2 has 69347 (> 99.9%) missing values Missing
opioids has 1252 (1.8%) missing values Missing
oxazepam_1 has 69343 (> 99.9%) missing values Missing
oxycodone_1 has 69190 (99.8%) missing values Missing
oxycodone_2 has 69351 (> 99.9%) missing values Missing
oxymorphone_1 has 69326 (> 99.9%) missing values Missing
oxymorphone_2 has 69358 (> 99.9%) missing values Missing
para-fluorobutyryl_1 has 69348 (> 99.9%) missing values Missing
pcp_1 has 69348 (> 99.9%) missing values Missing
pcp_2 has 69356 (> 99.9%) missing values Missing
phencyclidine_1 has 69103 (99.6%) missing values Missing
phencyclidine_2 has 69335 (> 99.9%) missing values Missing
phentermine_1 has 69352 (> 99.9%) missing values Missing
polysubstance_1 has 69354 (> 99.9%) missing values Missing
polysubstance_2 has 69341 (> 99.9%) missing values Missing
polysubstance_tag has 69336 (> 99.9%) missing values Missing
primary_cod has 815 (1.2%) missing values Missing
primarycause has 815 (1.2%) missing values Missing
primarycause_linea has 46767 (67.4%) missing values Missing
primarycause_lineb has 66113 (95.3%) missing values Missing
primarycause_linec has 69287 (99.9%) missing values Missing
propoxyphene_1 has 69358 (> 99.9%) missing values Missing
residence_city has 1906 (2.7%) missing values Missing
residence_zip has 1802 (2.6%) missing values Missing
secondarycause has 41485 (59.8%) missing values Missing
sedative_tag has 67194 (96.9%) missing values Missing
stimulant_tag has 64025 (92.3%) missing values Missing
tarpentadol_1 has 69358 (> 99.9%) missing values Missing
temazepam_1 has 69315 (99.9%) missing values Missing
tizanidine_1 has 69358 (> 99.9%) missing values Missing
topiramate_1 has 69317 (99.9%) missing values Missing
topiramate_2 has 69358 (> 99.9%) missing values Missing
toxic_tag has 69180 (99.7%) missing values Missing
tramadol_1 has 69031 (99.5%) missing values Missing
tramadol_2 has 69357 (> 99.9%) missing values Missing
u-47700_1 has 69316 (99.9%) missing values Missing
u-49900_1 has 69357 (> 99.9%) missing values Missing
utonitazene_1 has 69358 (> 99.9%) missing values Missing
valeryl_1 has 69341 (> 99.9%) missing values Missing
xylazine_1 has 69064 (99.6%) missing values Missing
xylazine_2 has 69355 (> 99.9%) missing values Missing
composite_latitude has 2086 (3.0%) missing values Missing
composite_longitude has 2086 (3.0%) missing values Missing
OBJECTID_left has 3864 (5.6%) missing values Missing
AGENCY has 3864 (5.6%) missing values Missing
AGENCY_DESC has 3864 (5.6%) missing values Missing
MUNICIPALITY has 4828 (7.0%) missing values Missing
COMMENTS has 68840 (99.3%) missing values Missing
SDELENGTH_SHAPE_ has 4230 (6.1%) missing values Missing
GlobalID has 3864 (5.6%) missing values Missing
created_user has 67027 (96.6%) missing values Missing
created_date has 67027 (96.6%) missing values Missing
last_edited_user has 3864 (5.6%) missing values Missing
last_edited_date has 3864 (5.6%) missing values Missing
muniCnclMmbr has 50793 (73.2%) missing values Missing
cbasOptIn has 6455 (9.3%) missing values Missing
SHAPE.STArea() has 3864 (5.6%) missing values Missing
SHAPE.STLength() has 3864 (5.6%) missing values Missing
pri_neigh has 28527 (41.1%) missing values Missing
sec_neigh has 28527 (41.1%) missing values Missing
shape_area has 28527 (41.1%) missing values Missing
shape_len has 28527 (41.1%) missing values Missing
OBJECTID_right has 69121 (99.7%) missing values Missing
CFNAME has 69121 (99.7%) missing values Missing
CFTYPE has 69121 (99.7%) missing values Missing
CFSUBTYPE has 69121 (99.7%) missing values Missing
ADDRESS has 69121 (99.7%) missing values Missing
GNISCODE has 69152 (99.7%) missing values Missing
COMMENT has 69352 (> 99.9%) missing values Missing
SOURCE has 69121 (99.7%) missing values Missing
Jurisdiction has 69141 (99.7%) missing values Missing
Community has 69121 (99.7%) missing values Missing
STATEFP_left has 2267 (3.3%) missing values Missing
COUNTYFP_left has 2267 (3.3%) missing values Missing
COUSUBFP has 2267 (3.3%) missing values Missing
COUSUBNS has 2267 (3.3%) missing values Missing
AFFGEOID has 2267 (3.3%) missing values Missing
GEOID_left has 2267 (3.3%) missing values Missing
NAME_left has 2267 (3.3%) missing values Missing
LSAD has 2267 (3.3%) missing values Missing
ALAND_left has 2267 (3.3%) missing values Missing
AWATER_left has 2267 (3.3%) missing values Missing
STATEFP_right has 2217 (3.2%) missing values Missing
COUNTYFP_right has 2217 (3.2%) missing values Missing
TRACTCE has 2217 (3.2%) missing values Missing
GEOID_right has 2217 (3.2%) missing values Missing
NAME_right has 2217 (3.2%) missing values Missing
NAMELSAD has 2217 (3.2%) missing values Missing
MTFCC has 2217 (3.2%) missing values Missing
FUNCSTAT has 2217 (3.2%) missing values Missing
ALAND_right has 2217 (3.2%) missing values Missing
AWATER_right has 2217 (3.2%) missing values Missing
INTPTLAT has 2217 (3.2%) missing values Missing
INTPTLON has 2217 (3.2%) missing values Missing
GEOID has 35983 (51.9%) missing values Missing
GEOG has 35983 (51.9%) missing values Missing
TOT_POP has 35983 (51.9%) missing values Missing
POP_HH has 35983 (51.9%) missing values Missing
POP_GQ has 35983 (51.9%) missing values Missing
HISP has 35983 (51.9%) missing values Missing
WHITE has 35983 (51.9%) missing values Missing
BLACK has 35983 (51.9%) missing values Missing
ASIAN has 35983 (51.9%) missing values Missing
OTHER has 35983 (51.9%) missing values Missing
HU_TOT has 35983 (51.9%) missing values Missing
TOT_HH has 35983 (51.9%) missing values Missing
VAC_HU has 35983 (51.9%) missing values Missing
HH_SIZE has 35983 (51.9%) missing values Missing
index_right has 2227 (3.2%) missing values Missing
FIRST_COUN has 2227 (3.2%) missing values Missing
LANDUSE has 2227 (3.2%) missing values Missing
LANDUSE2 has 69294 (99.9%) missing values Missing
OS_MGMT has 68862 (99.3%) missing values Missing
FAC_NAME has 69155 (99.7%) missing values Missing
PLATTED has 69351 (> 99.9%) missing values Missing
MODIFIER has 69293 (99.9%) missing values Missing
Shape_Leng has 2227 (3.2%) missing values Missing
Shape_Area has 2227 (3.2%) missing values Missing
landuse_name has 2227 (3.2%) missing values Missing
landuse_sub_name has 2227 (3.2%) missing values Missing
landuse_major_name has 2227 (3.2%) missing values Missing
death_street has 9314 (13.4%) missing values Missing
death_city has 9635 (13.9%) missing values Missing
death_county has 35330 (50.9%) missing values Missing
death_state has 9828 (14.2%) missing values Missing
death_zip has 10761 (15.5%) missing values Missing
death_location has 32243 (46.5%) missing values Missing
death_location_1 has 14487 (20.9%) missing values Missing
Shape_Area is highly skewed (γ1 = 26.60461822) Skewed
CaseIdentifier has unique values Unique
__id has unique values Unique
casenumber has unique values Unique
objectid has unique values Unique
incident_zip is an unsupported type, check if it needs cleaning or further analysis Unsupported
location_address is an unsupported type, check if it needs cleaning or further analysis Unsupported
location_city is an unsupported type, check if it needs cleaning or further analysis Unsupported
location_state is an unsupported type, check if it needs cleaning or further analysis Unsupported
location_zip is an unsupported type, check if it needs cleaning or further analysis Unsupported
residence_zip is an unsupported type, check if it needs cleaning or further analysis Unsupported
LANDUSE2 is an unsupported type, check if it needs cleaning or further analysis Unsupported
death_zip is an unsupported type, check if it needs cleaning or further analysis Unsupported
covid_related has 53239 (76.8%) zeros Zeros
gunrelated has 60878 (87.8%) zeros Zeros
opioids has 57654 (83.1%) zeros Zeros
AWATER_left has 4264 (6.1%) zeros Zeros
AWATER_right has 52387 (75.5%) zeros Zeros
incident_matches_death has 69116 (99.6%) zeros Zeros
hotel has 68717 (99.1%) zeros Zeros
repeated_lat_long has 53589 (77.3%) zeros Zeros

Reproduction

Analysis started2022-09-15 20:47:58.921014
Analysis finished2022-09-15 20:48:01.175268
Duration2.25 seconds
Software versionpandas-profiling v3.2.0
Download configurationconfig.json

Variables

4-fibf_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.262118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:01.291776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

CaseIdentifier
Real number (ℝ≥0)

UNIQUE

Distinct69359
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34679
Minimum0
Maximum69358
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.326357image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile3467.9
Q117339.5
median34679
Q352018.5
95-th percentile65890.1
Maximum69358
Range69358
Interquartile range (IQR)34679

Descriptive statistics

Standard deviation20022.363
Coefficient of variation (CV)0.5773627555
Kurtosis-1.2
Mean34679
Median Absolute Deviation (MAD)17340
Skewness0
Sum2405300761
Variance400895020
MonotonicityStrictly increasing
2022-09-15T16:48:01.377729image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
01
 
< 0.1%
462441
 
< 0.1%
462301
 
< 0.1%
462311
 
< 0.1%
462321
 
< 0.1%
462331
 
< 0.1%
462341
 
< 0.1%
462351
 
< 0.1%
462361
 
< 0.1%
462371
 
< 0.1%
Other values (69349)69349
> 99.9%
ValueCountFrequency (%)
01
< 0.1%
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
ValueCountFrequency (%)
693581
< 0.1%
693571
< 0.1%
693561
< 0.1%
693551
< 0.1%
693541
< 0.1%

__id
Categorical

HIGH CARDINALITY
UNIQUE

Distinct69359
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size542.0 KiB
row-zqhu_7sdq~t9fr
 
1
row-c4vi_5356~xsim
 
1
row-dvvp_ukat-kz7f
 
1
row-wysm-hi6j_8bj9
 
1
row-ig4h.hb3m_x8xr
 
1
Other values (69354)
69354 

Unique

Unique69359 ?
Unique (%)100.0%

Sample

1st rowrow-zqhu_7sdq~t9fr
2nd rowrow-4vi5~7kpn-2xnv
3rd rowrow-59mk_c9af~xd4h
4th rowrow-m25n_de74~ef7e
5th rowrow-d5g9~u8t6.hq5i

Common Values

ValueCountFrequency (%)
row-zqhu_7sdq~t9fr1
 
< 0.1%
row-c4vi_5356~xsim1
 
< 0.1%
row-dvvp_ukat-kz7f1
 
< 0.1%
row-wysm-hi6j_8bj91
 
< 0.1%
row-ig4h.hb3m_x8xr1
 
< 0.1%
row-dvjy.4dib.hf3b1
 
< 0.1%
row-uagr~h4dr~vd441
 
< 0.1%
row-tb6r_9c5s-rk4b1
 
< 0.1%
row-59jw_7y9q.nuy61
 
< 0.1%
row-dqqs-s338~uyvz1
 
< 0.1%
Other values (69349)69349
> 99.9%

acetyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing68335
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.410380image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum1024
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.463394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11024
 
1.5%
(Missing)68335
98.5%
ValueCountFrequency (%)
11024
1.5%
ValueCountFrequency (%)
11024
1.5%

acetyl_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)11.1%
Missing69350
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.489074image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum9
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.513856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
19
 
< 0.1%
(Missing)69350
> 99.9%
ValueCountFrequency (%)
19
< 0.1%
ValueCountFrequency (%)
19
< 0.1%

acetylsalicylic_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.539035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.566155image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

age
Real number (ℝ≥0)

Distinct110
Distinct (%)0.2%
Missing373
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean56.2754182
Minimum0
Maximum109
Zeros680
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.602465image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile21
Q141
median58
Q372
95-th percentile90
Maximum109
Range109
Interquartile range (IQR)31

Descriptive statistics

Standard deviation21.43663801
Coefficient of variation (CV)0.3809236554
Kurtosis-0.5366032761
Mean56.2754182
Median Absolute Deviation (MAD)15
Skewness-0.2455203313
Sum3882216
Variance459.5294492
MonotonicityNot monotonic
2022-09-15T16:48:01.645338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
581458
 
2.1%
591436
 
2.1%
601390
 
2.0%
611389
 
2.0%
621386
 
2.0%
571348
 
1.9%
631346
 
1.9%
641343
 
1.9%
561313
 
1.9%
651290
 
1.9%
Other values (100)55287
79.7%
ValueCountFrequency (%)
0680
1.0%
176
 
0.1%
269
 
0.1%
348
 
0.1%
430
 
< 0.1%
ValueCountFrequency (%)
1091
 
< 0.1%
1081
 
< 0.1%
1071
 
< 0.1%
1064
< 0.1%
1058
< 0.1%

alcohol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.3%
Missing69043
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.676253image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum316
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.702900image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1316
 
0.5%
(Missing)69043
99.5%
ValueCountFrequency (%)
1316
0.5%
ValueCountFrequency (%)
1316
0.5%

alcohol_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.4%
Missing69288
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.728877image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum71
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.755560image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
171
 
0.1%
(Missing)69288
99.9%
ValueCountFrequency (%)
171
0.1%
ValueCountFrequency (%)
171
0.1%

alprazolam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing68331
Missing (%)98.5%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.781715image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum1028
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.808059image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11028
 
1.5%
(Missing)68331
98.5%
ValueCountFrequency (%)
11028
1.5%
ValueCountFrequency (%)
11028
1.5%

alprazolam_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)7.1%
Missing69345
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.833767image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum14
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.860427image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
114
 
< 0.1%
(Missing)69345
> 99.9%
ValueCountFrequency (%)
114
< 0.1%
ValueCountFrequency (%)
114
< 0.1%

amphetamine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.5%
Missing69153
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.919885image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum206
Variance0
MonotonicityIncreasing
2022-09-15T16:48:01.947333image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1206
 
0.3%
(Missing)69153
99.7%
ValueCountFrequency (%)
1206
0.3%
ValueCountFrequency (%)
1206
0.3%

amphetamine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)6.7%
Missing69344
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:01.973671image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum15
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.000592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
115
 
< 0.1%
(Missing)69344
> 99.9%
ValueCountFrequency (%)
115
< 0.1%
ValueCountFrequency (%)
115
< 0.1%

anpp_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.026607image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.054414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

aspirin_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.081209image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:02.107240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

aspirin_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)33.3%
Missing69356
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.133408image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.159859image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13
 
< 0.1%
(Missing)69356
> 99.9%
ValueCountFrequency (%)
13
< 0.1%
ValueCountFrequency (%)
13
< 0.1%

average_distance
Real number (ℝ≥0)

MISSING

Distinct3869
Distinct (%)11.5%
Missing35722
Missing (%)51.5%
Infinite0
Infinite (%)0.0%
Mean21.95806493
Minimum9.33
Maximum66.65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.194335image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum9.33
5-th percentile13.52
Q116.18
median19.18
Q324.82
95-th percentile40.65
Maximum66.65
Range57.32
Interquartile range (IQR)8.64

Descriptive statistics

Standard deviation8.346413097
Coefficient of variation (CV)0.3801069504
Kurtosis1.873995505
Mean21.95806493
Median Absolute Deviation (MAD)3.56
Skewness1.479442475
Sum738603.43
Variance69.66261159
MonotonicityNot monotonic
2022-09-15T16:48:02.233584image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15.7361
 
0.1%
16.8760
 
0.1%
15.8759
 
0.1%
15.9758
 
0.1%
15.7755
 
0.1%
15.3753
 
0.1%
15.5453
 
0.1%
16.153
 
0.1%
15.1252
 
0.1%
15.4152
 
0.1%
Other values (3859)33081
47.7%
(Missing)35722
51.5%
ValueCountFrequency (%)
9.331
< 0.1%
9.591
< 0.1%
9.651
< 0.1%
9.821
< 0.1%
9.861
< 0.1%
ValueCountFrequency (%)
66.651
< 0.1%
64.911
< 0.1%
64.61
< 0.1%
64.492
< 0.1%
63.921
< 0.1%

barbiturates_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)25.0%
Missing69355
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.264738image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.292271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14
 
< 0.1%
(Missing)69355
> 99.9%
ValueCountFrequency (%)
14
< 0.1%
ValueCountFrequency (%)
14
< 0.1%

benzo_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing67453
Missing (%)97.3%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.318970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum1906
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.346304image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11906
 
2.7%
(Missing)67453
97.3%
ValueCountFrequency (%)
11906
2.7%
ValueCountFrequency (%)
11906
2.7%

benzodiazepine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.5%
Missing69143
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.372754image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum216
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.397924image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1216
 
0.3%
(Missing)69143
99.7%
ValueCountFrequency (%)
1216
0.3%
ValueCountFrequency (%)
1216
0.3%

benzodiazepine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)10.0%
Missing69349
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.423697image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum10
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.498162image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
110
 
< 0.1%
(Missing)69349
> 99.9%
ValueCountFrequency (%)
110
< 0.1%
ValueCountFrequency (%)
110
< 0.1%

buprenorphine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.2%
Missing69277
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.523925image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum82
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.551064image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
182
 
0.1%
(Missing)69277
99.9%
ValueCountFrequency (%)
182
0.1%
ValueCountFrequency (%)
182
0.1%

buprenorphine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.577426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:02.603342image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

butonitazene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.629170image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:02.655076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

butyryl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.681310image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.708872image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

cannabis_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.735524image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:02.761427image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

cannabis_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.787103image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:02.813038image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

carfentanil_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.2%
Missing69313
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.838801image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum46
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.863843image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
146
 
0.1%
(Missing)69313
99.9%
ValueCountFrequency (%)
146
0.1%
ValueCountFrequency (%)
146
0.1%

carisoprodol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)6.2%
Missing69343
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.889224image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum16
Variance0
MonotonicityIncreasing
2022-09-15T16:48:02.916435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
116
 
< 0.1%
(Missing)69343
> 99.9%
ValueCountFrequency (%)
116
< 0.1%
ValueCountFrequency (%)
116
< 0.1%

casenumber
Categorical

HIGH CARDINALITY
UNIQUE

Distinct69359
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size542.0 KiB
ME2020-05711
 
1
ME2020-13499
 
1
ME2020-13447
 
1
ME2020-13466
 
1
ME2020-13475
 
1
Other values (69354)
69354 

Unique

Unique69359 ?
Unique (%)100.0%

Sample

1st rowME2020-05711
2nd rowME2021-03779
3rd rowME2014-00627
4th rowME2014-00649
5th rowME2014-00712

Common Values

ValueCountFrequency (%)
ME2020-057111
 
< 0.1%
ME2020-134991
 
< 0.1%
ME2020-134471
 
< 0.1%
ME2020-134661
 
< 0.1%
ME2020-134751
 
< 0.1%
ME2020-134741
 
< 0.1%
ME2020-134651
 
< 0.1%
ME2020-134851
 
< 0.1%
ME2020-134901
 
< 0.1%
ME2020-134671
 
< 0.1%
Other values (69349)69349
> 99.9%

chi_commarea
Categorical

HIGH CARDINALITY
MISSING

Distinct77
Distinct (%)0.2%
Missing31017
Missing (%)44.7%
Memory size542.0 KiB
AUSTIN
 
2417
SOUTH SHORE
 
1336
HUMBOLDT PARK
 
1213
NORTH LAWNDALE
 
1133
ROSELAND
 
1055
Other values (72)
31188 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNEAR NORTH SIDE
2nd rowAUBURN GRESHAM
3rd rowWEST PULLMAN
4th rowCHICAGO LAWN
5th rowWEST ENGLEWOOD

Common Values

ValueCountFrequency (%)
AUSTIN2417
 
3.5%
SOUTH SHORE1336
 
1.9%
HUMBOLDT PARK1213
 
1.7%
NORTH LAWNDALE1133
 
1.6%
ROSELAND1055
 
1.5%
AUBURN GRESHAM1011
 
1.5%
NEAR NORTH SIDE985
 
1.4%
UPTOWN969
 
1.4%
SOUTH LAWNDALE931
 
1.3%
WEST GARFIELD PARK925
 
1.3%
Other values (67)26367
38.0%
(Missing)31017
44.7%

chi_ward
Real number (ℝ≥0)

MISSING

Distinct50
Distinct (%)0.1%
Missing31020
Missing (%)44.7%
Infinite0
Infinite (%)0.0%
Mean23.9964527
Minimum1
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:02.952707image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q112
median24
Q335
95-th percentile48
Maximum50
Range49
Interquartile range (IQR)23

Descriptive statistics

Standard deviation13.86216318
Coefficient of variation (CV)0.5776755153
Kurtosis-1.061466915
Mean23.9964527
Median Absolute Deviation (MAD)12
Skewness0.1347539291
Sum920000
Variance192.159568
MonotonicityNot monotonic
2022-09-15T16:48:02.995348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
281935
 
2.8%
271531
 
2.2%
241509
 
2.2%
371281
 
1.8%
61223
 
1.8%
71195
 
1.7%
81171
 
1.7%
161117
 
1.6%
341108
 
1.6%
201104
 
1.6%
Other values (40)25165
36.3%
(Missing)31020
44.7%
ValueCountFrequency (%)
1482
0.7%
2558
0.8%
31038
1.5%
4790
1.1%
5877
1.3%
ValueCountFrequency (%)
50518
0.7%
49749
1.1%
48849
1.2%
47365
0.5%
46757
1.1%

chlordiazepoxide_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.2%
Missing69335
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.026339image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum24
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.051886image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
124
 
< 0.1%
(Missing)69335
> 99.9%
ValueCountFrequency (%)
124
< 0.1%
ValueCountFrequency (%)
124
< 0.1%

clonazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.2%
Missing68931
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.077260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum428
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.104020image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1428
 
0.6%
(Missing)68931
99.4%
ValueCountFrequency (%)
1428
0.6%
ValueCountFrequency (%)
1428
0.6%

clonazepam_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)14.3%
Missing69352
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.131348image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum7
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.220353image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
17
 
< 0.1%
(Missing)69352
> 99.9%
ValueCountFrequency (%)
17
< 0.1%
ValueCountFrequency (%)
17
< 0.1%

closest_medical_center_km
Real number (ℝ≥0)

MISSING

Distinct2202
Distinct (%)3.3%
Missing2086
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean4.298505641
Minimum0
Maximum28.94
Zeros5
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.256076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.64
Q11.74
median3.17
Q35.39
95-th percentile12.7
Maximum28.94
Range28.94
Interquartile range (IQR)3.65

Descriptive statistics

Standard deviation3.836743205
Coefficient of variation (CV)0.8925760544
Kurtosis5.485424126
Mean4.298505641
Median Absolute Deviation (MAD)1.68
Skewness2.061364184
Sum289173.37
Variance14.72059842
MonotonicityNot monotonic
2022-09-15T16:48:03.298056image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.87194
 
0.3%
0.91194
 
0.3%
2.35190
 
0.3%
1.66189
 
0.3%
1.6180
 
0.3%
1.34178
 
0.3%
1.94173
 
0.2%
2.14171
 
0.2%
2.61168
 
0.2%
1.92168
 
0.2%
Other values (2192)65468
94.4%
(Missing)2086
 
3.0%
ValueCountFrequency (%)
05
 
< 0.1%
0.013
 
< 0.1%
0.0235
0.1%
0.031
 
< 0.1%
0.0430
< 0.1%
ValueCountFrequency (%)
28.941
 
< 0.1%
28.561
 
< 0.1%
28.421
 
< 0.1%
28.271
 
< 0.1%
27.8311
< 0.1%

closest_pharmacy_km
Real number (ℝ≥0)

MISSING

Distinct957
Distinct (%)1.4%
Missing2086
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean0.7329753393
Minimum0
Maximum33.46
Zeros132
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.339177image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.1
Q10.28
median0.49
Q30.8
95-th percentile1.78
Maximum33.46
Range33.46
Interquartile range (IQR)0.52

Descriptive statistics

Standard deviation1.244826575
Coefficient of variation (CV)1.698319859
Kurtosis162.1838861
Mean0.7329753393
Median Absolute Deviation (MAD)0.25
Skewness10.30076855
Sum49309.45
Variance1.549593202
MonotonicityNot monotonic
2022-09-15T16:48:03.379619image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.23887
 
1.3%
0.35884
 
1.3%
0.25869
 
1.3%
0.27862
 
1.2%
0.39853
 
1.2%
0.24844
 
1.2%
0.36837
 
1.2%
0.29835
 
1.2%
0.31834
 
1.2%
0.38833
 
1.2%
Other values (947)58735
84.7%
(Missing)2086
 
3.0%
ValueCountFrequency (%)
0132
0.2%
0.01148
0.2%
0.02167
0.2%
0.03191
0.3%
0.04318
0.5%
ValueCountFrequency (%)
33.461
 
< 0.1%
31.91
 
< 0.1%
30.98
< 0.1%
29.911
 
< 0.1%
29.761
 
< 0.1%

cocaine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing65082
Missing (%)93.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.410616image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4277
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.437545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14277
 
6.2%
(Missing)65082
93.8%
ValueCountFrequency (%)
14277
6.2%
ValueCountFrequency (%)
14277
6.2%

cocaine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.2%
Missing68830
Missing (%)99.2%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.464422image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum529
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.489934image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1529
 
0.8%
(Missing)68830
99.2%
ValueCountFrequency (%)
1529
0.8%
ValueCountFrequency (%)
1529
0.8%

codeine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.6%
Missing69298
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.516602image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum61
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.542655image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
161
 
0.1%
(Missing)69298
99.9%
ValueCountFrequency (%)
161
0.1%
ValueCountFrequency (%)
161
0.1%

codeine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)25.0%
Missing69355
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.568341image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.595063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14
 
< 0.1%
(Missing)69355
> 99.9%
ValueCountFrequency (%)
14
< 0.1%
ValueCountFrequency (%)
14
< 0.1%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
False
68901 
True
 
458
ValueCountFrequency (%)
False68901
99.3%
True458
 
0.7%
2022-09-15T16:48:03.632837image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

commissioner_district
Real number (ℝ≥0)

MISSING

Distinct17
Distinct (%)< 0.1%
Missing8907
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean7.49273804
Minimum1
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.658604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q13
median7
Q311
95-th percentile16
Maximum17
Range16
Interquartile range (IQR)8

Descriptive statistics

Standard deviation4.969640027
Coefficient of variation (CV)0.6632608801
Kurtosis-1.098382393
Mean7.49273804
Median Absolute Deviation (MAD)4
Skewness0.3915260902
Sum452951
Variance24.697322
MonotonicityNot monotonic
2022-09-15T16:48:03.690718image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
26691
 
9.6%
15811
 
8.4%
35059
 
7.3%
54658
 
6.7%
44590
 
6.6%
113376
 
4.9%
103304
 
4.8%
73065
 
4.4%
63061
 
4.4%
82971
 
4.3%
Other values (7)17866
25.8%
(Missing)8907
12.8%
ValueCountFrequency (%)
15811
8.4%
26691
9.6%
35059
7.3%
44590
6.6%
54658
6.7%
ValueCountFrequency (%)
172685
3.9%
162742
4.0%
151996
2.9%
142135
3.1%
132748
4.0%

corona_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing54938
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.720019image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum14421
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.746600image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
114421
 
20.8%
(Missing)54938
79.2%
ValueCountFrequency (%)
114421
20.8%
ValueCountFrequency (%)
114421
20.8%

corona_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing68445
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.772883image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum914
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.798181image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1914
 
1.3%
(Missing)68445
98.7%
ValueCountFrequency (%)
1914
1.3%
ValueCountFrequency (%)
1914
1.3%

coronavirus_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)3.6%
Missing69331
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.824335image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum28
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.850424image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
128
 
< 0.1%
(Missing)69331
> 99.9%
ValueCountFrequency (%)
128
< 0.1%
ValueCountFrequency (%)
128
< 0.1%

coronavirus_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)20.0%
Missing69354
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.876322image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.902006image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15
 
< 0.1%
(Missing)69354
> 99.9%
ValueCountFrequency (%)
15
< 0.1%
ValueCountFrequency (%)
15
< 0.1%

covid-19_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing54914
Missing (%)79.2%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.927944image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum14445
Variance0
MonotonicityIncreasing
2022-09-15T16:48:03.954051image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
114445
 
20.8%
(Missing)54914
79.2%
ValueCountFrequency (%)
114445
20.8%
ValueCountFrequency (%)
114445
20.8%

covid-19_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing68454
Missing (%)98.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:03.980454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum905
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.087262image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1905
 
1.3%
(Missing)68454
98.7%
ValueCountFrequency (%)
1905
1.3%
ValueCountFrequency (%)
1905
1.3%

covid_related
Real number (ℝ≥0)

MISSING
ZEROS

Distinct2
Distinct (%)< 0.1%
Missing760
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean0.2239099695
Minimum0
Maximum1
Zeros53239
Zeros (%)76.8%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.113014image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4168654799
Coefficient of variation (CV)1.861754886
Kurtosis-0.2453393865
Mean0.2239099695
Median Absolute Deviation (MAD)0
Skewness1.324638731
Sum15360
Variance0.1737768283
MonotonicityNot monotonic
2022-09-15T16:48:04.140650image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
053239
76.8%
115360
 
22.1%
(Missing)760
 
1.1%
ValueCountFrequency (%)
053239
76.8%
115360
 
22.1%
ValueCountFrequency (%)
115360
 
22.1%
053239
76.8%

covid_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing53989
Missing (%)77.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.167081image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum15370
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.193924image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
115370
 
22.2%
(Missing)53989
77.8%
ValueCountFrequency (%)
115370
22.2%
ValueCountFrequency (%)
115370
22.2%

cyclobenzaprine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.6%
Missing69205
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.220840image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum154
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.247607image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1154
 
0.2%
(Missing)69205
99.8%
ValueCountFrequency (%)
1154
0.2%
ValueCountFrequency (%)
1154
0.2%

cyclobenzaprine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.273827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:04.299217image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

cyclopropyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.8%
Missing69236
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.325024image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum123
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.351316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1123
 
0.2%
(Missing)69236
99.8%
ValueCountFrequency (%)
1123
0.2%
ValueCountFrequency (%)
1123
0.2%

death_date
Categorical

HIGH CARDINALITY

Distinct2970
Distinct (%)4.3%
Missing61
Missing (%)0.1%
Memory size542.0 KiB
2020-05-07
 
111
2020-05-03
 
109
2020-05-09
 
108
2020-05-04
 
108
2020-05-02
 
106
Other values (2965)
68756 

Unique

Unique15 ?
Unique (%)< 0.1%

Sample

1st row2020-05-15
2nd row2021-04-09
3rd row2014-09-21
4th row2014-09-22
5th row2014-09-27

Common Values

ValueCountFrequency (%)
2020-05-07111
 
0.2%
2020-05-03109
 
0.2%
2020-05-09108
 
0.2%
2020-05-04108
 
0.2%
2020-05-02106
 
0.2%
2020-05-14105
 
0.2%
2022-01-12104
 
0.1%
2020-05-05103
 
0.1%
2020-05-15102
 
0.1%
2020-04-28101
 
0.1%
Other values (2960)68241
98.4%

despropionyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing65484
Missing (%)94.4%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.377526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3875
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.404245image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13875
 
5.6%
(Missing)65484
94.4%
ValueCountFrequency (%)
13875
5.6%
ValueCountFrequency (%)
13875
5.6%

despropionyl_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.2%
Missing69335
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.431352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum24
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.457279image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
124
 
< 0.1%
(Missing)69335
> 99.9%
ValueCountFrequency (%)
124
< 0.1%
ValueCountFrequency (%)
124
< 0.1%

dextromethorphan_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)3.7%
Missing69332
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.483154image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum27
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.509035image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
127
 
< 0.1%
(Missing)69332
> 99.9%
ValueCountFrequency (%)
127
< 0.1%
ValueCountFrequency (%)
127
< 0.1%

dextromethorphan_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.534896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:04.560943image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

dextrorphan_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.586913image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:04.612881image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

diazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69114
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.639067image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum245
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.665113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1245
 
0.4%
(Missing)69114
99.6%
ValueCountFrequency (%)
1245
0.4%
ValueCountFrequency (%)
1245
0.4%

diazepam_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.690776image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:04.716373image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

dihydrocodeine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)6.7%
Missing69344
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.742385image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum15
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.769133image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
115
 
< 0.1%
(Missing)69344
> 99.9%
ValueCountFrequency (%)
115
< 0.1%
ValueCountFrequency (%)
115
< 0.1%

drug_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing56849
Missing (%)82.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.794926image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum12510
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.820772image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
112510
 
18.0%
(Missing)56849
82.0%
ValueCountFrequency (%)
112510
18.0%
ValueCountFrequency (%)
112510
18.0%

estazolam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.847317image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.874155image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

eth_alc_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing65660
Missing (%)94.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.900510image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3699
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.926396image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13699
 
5.3%
(Missing)65660
94.7%
ValueCountFrequency (%)
13699
5.3%
ValueCountFrequency (%)
13699
5.3%

ethanol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing66293
Missing (%)95.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:04.952743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3066
Variance0
MonotonicityIncreasing
2022-09-15T16:48:04.978942image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13066
 
4.4%
(Missing)66293
95.6%
ValueCountFrequency (%)
13066
4.4%
ValueCountFrequency (%)
13066
4.4%

ethanol_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69107
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.004896image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum252
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.030290image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1252
 
0.4%
(Missing)69107
99.6%
ValueCountFrequency (%)
1252
0.4%
ValueCountFrequency (%)
1252
0.4%

fen_analog_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing64587
Missing (%)93.1%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.055838image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4772
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.081580image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14772
 
6.9%
(Missing)64587
93.1%
ValueCountFrequency (%)
14772
6.9%
ValueCountFrequency (%)
14772
6.9%

fentanyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing62223
Missing (%)89.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.106972image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum7136
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.239269image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
17136
 
10.3%
(Missing)62223
89.7%
ValueCountFrequency (%)
17136
10.3%
ValueCountFrequency (%)
17136
10.3%

fentanyl_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.2%
Missing69279
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.266182image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum80
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.292964image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
180
 
0.1%
(Missing)69279
99.9%
ValueCountFrequency (%)
180
0.1%
ValueCountFrequency (%)
180
0.1%

fentanyl_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing62120
Missing (%)89.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.319135image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum7239
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.345926image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
17239
 
10.4%
(Missing)62120
89.6%
ValueCountFrequency (%)
17239
10.4%
ValueCountFrequency (%)
17239
10.4%

fibf_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)33.3%
Missing69356
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.372185image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.398124image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13
 
< 0.1%
(Missing)69356
> 99.9%
ValueCountFrequency (%)
13
< 0.1%
ValueCountFrequency (%)
13
< 0.1%

flunitazene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.423859image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.450678image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

flurazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)20.0%
Missing69354
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.477096image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.503093image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15
 
< 0.1%
(Missing)69354
> 99.9%
ValueCountFrequency (%)
15
< 0.1%
ValueCountFrequency (%)
15
< 0.1%

furanyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.5%
Missing69149
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.528773image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum210
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.555483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1210
 
0.3%
(Missing)69149
99.7%
ValueCountFrequency (%)
1210
0.3%
ValueCountFrequency (%)
1210
0.3%

furanyl_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.581834image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:05.607474image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

gender
Categorical

Distinct3
Distinct (%)< 0.1%
Missing249
Missing (%)0.4%
Memory size542.0 KiB
Male
47765 
Female
21306 
Unknown
 
39

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemale
2nd rowFemale
3rd rowMale
4th rowMale
5th rowMale

Common Values

ValueCountFrequency (%)
Male47765
68.9%
Female21306
30.7%
Unknown39
 
0.1%
(Missing)249
 
0.4%

Category Frequency Plot

2022-09-15T16:48:05.639371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

geocoded_latitude
Real number (ℝ≥0)

MISSING

Distinct5307
Distinct (%)77.9%
Missing62547
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean41.83288313
Minimum41.40003502
Maximum42.19982043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.674696image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.40003502
5-th percentile41.49718503
Q141.70275243
median41.85758976
Q341.97589751
95-th percentile42.14228965
Maximum42.19982043
Range0.7997854034
Interquartile range (IQR)0.2731450787

Descriptive statistics

Standard deviation0.1888255425
Coefficient of variation (CV)0.004513806566
Kurtosis-0.6474869922
Mean41.83288313
Median Absolute Deviation (MAD)0.1309552726
Skewness-0.2684868249
Sum284965.5999
Variance0.03565508551
MonotonicityNot monotonic
2022-09-15T16:48:05.717394image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.997574744
 
0.1%
41.9785707734
 
< 0.1%
42.1621701619
 
< 0.1%
42.1675916217
 
< 0.1%
41.4030113214
 
< 0.1%
42.1852000514
 
< 0.1%
42.0389944913
 
< 0.1%
41.8078119612
 
< 0.1%
42.1558059112
 
< 0.1%
42.1672036211
 
< 0.1%
Other values (5297)6622
 
9.5%
(Missing)62547
90.2%
ValueCountFrequency (%)
41.400035022
 
< 0.1%
41.401155013
 
< 0.1%
41.40276911
 
< 0.1%
41.4030113214
< 0.1%
41.404675271
 
< 0.1%
ValueCountFrequency (%)
42.199820431
< 0.1%
42.199799081
< 0.1%
42.199537271
< 0.1%
42.199110971
< 0.1%
42.198984991
< 0.1%

geocoded_longitude
Real number (ℝ)

MISSING

Distinct5308
Distinct (%)77.9%
Missing62547
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean-87.80381554
Minimum-88.29986998
Maximum-87.50000326
Zeros0
Zeros (%)0.0%
Negative6812
Negative (%)9.8%
Memory size542.0 KiB
2022-09-15T16:48:05.759298image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-88.29986998
5-th percentile-88.17133703
Q1-87.9153888
median-87.76002242
Q3-87.65642886
95-th percentile-87.579609
Maximum-87.50000326
Range0.7998667206
Interquartile range (IQR)0.2589599359

Descriptive statistics

Standard deviation0.1849161877
Coefficient of variation (CV)-0.0021060154
Kurtosis-0.107372838
Mean-87.80381554
Median Absolute Deviation (MAD)0.1207186003
Skewness-0.7942365637
Sum-598119.5915
Variance0.03419399649
MonotonicityNot monotonic
2022-09-15T16:48:05.801142image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.887646444
 
0.1%
-87.8802495734
 
< 0.1%
-87.9862739619
 
< 0.1%
-88.0206397617
 
< 0.1%
-87.8226149114
 
< 0.1%
-87.6270217914
 
< 0.1%
-87.8833069713
 
< 0.1%
-87.6162973412
 
< 0.1%
-87.9562284412
 
< 0.1%
-87.58037511
 
< 0.1%
Other values (5298)6622
 
9.5%
(Missing)62547
90.2%
ValueCountFrequency (%)
-88.299869981
 
< 0.1%
-88.299814951
 
< 0.1%
-88.299664951
 
< 0.1%
-88.29954491
 
< 0.1%
-88.299369815
< 0.1%
ValueCountFrequency (%)
-87.500003261
< 0.1%
-87.500029951
< 0.1%
-87.500050311
< 0.1%
-87.500079971
< 0.1%
-87.500114941
< 0.1%

geocoded_matched_address
Categorical

HIGH CARDINALITY
MISSING

Distinct5386
Distinct (%)79.1%
Missing62547
Missing (%)90.2%
Memory size542.0 KiB
60666, Chicago, Illinois
 
44
10000 W O'Hare Ave, Chicago, Illinois, 60666
 
34
1666 Checker Rd, Lake Zurich, Illinois, 60047
 
19
2308 Old Hicks Rd, Lake Zurich, Illinois, 60047
 
17
60401, Beecher, Illinois
 
14
Other values (5381)
6684 

Unique

Unique4744 ?
Unique (%)69.6%

Sample

1st row10000 W O'Hare Ave, Chicago, Illinois, 60666
2nd row424 S Hebbard St, Joliet, Illinois, 60433
3rd row2113 W 18th Pl, Chicago, Illinois, 60608
4th row6826 S Anthony Ave, Chicago, Illinois, 60637
5th row1401 W 80th St, #3, Chicago, Illinois, 60620

Common Values

ValueCountFrequency (%)
60666, Chicago, Illinois44
 
0.1%
10000 W O'Hare Ave, Chicago, Illinois, 6066634
 
< 0.1%
1666 Checker Rd, Lake Zurich, Illinois, 6004719
 
< 0.1%
2308 Old Hicks Rd, Lake Zurich, Illinois, 6004717
 
< 0.1%
60401, Beecher, Illinois14
 
< 0.1%
Skokie Valley Rd, Highland Park, Illinois, 6003514
 
< 0.1%
150 Weiland Rd, Buffalo Grove, Illinois, 6008912
 
< 0.1%
3705 Deerfield Rd, Deerfield, Illinois, 6001511
 
< 0.1%
300 N River Rd, Des Plaines, Illinois, 6001611
 
< 0.1%
60617, Chicago, Illinois11
 
< 0.1%
Other values (5376)6625
 
9.6%
(Missing)62547
90.2%

geocoded_score
Real number (ℝ≥0)

MISSING

Distinct1610
Distinct (%)23.6%
Missing62547
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean92.48754257
Minimum70
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.842782image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum70
5-th percentile77
Q187.5375
median95.63
Q399.3075
95-th percentile100
Maximum100
Range30
Interquartile range (IQR)11.77

Descriptive statistics

Standard deviation7.943542301
Coefficient of variation (CV)0.0858876999
Kurtosis-0.3097496106
Mean92.48754257
Median Absolute Deviation (MAD)4.37
Skewness-0.9538108115
Sum630025.14
Variance63.09986429
MonotonicityNot monotonic
2022-09-15T16:48:05.884570image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001450
 
2.1%
77265
 
0.4%
98.5379
 
0.1%
99.4362
 
0.1%
8051
 
0.1%
98.951
 
0.1%
98.5151
 
0.1%
99.545
 
0.1%
97.5944
 
0.1%
96.3228
 
< 0.1%
Other values (1600)4686
 
6.8%
(Missing)62547
90.2%
ValueCountFrequency (%)
705
< 0.1%
70.031
 
< 0.1%
70.072
 
< 0.1%
70.083
< 0.1%
70.141
 
< 0.1%
ValueCountFrequency (%)
1001450
2.1%
99.9910
 
< 0.1%
99.982
 
< 0.1%
99.931
 
< 0.1%
99.911
 
< 0.1%

gunrelated
Real number (ℝ≥0)

MISSING
ZEROS

Distinct2
Distinct (%)< 0.1%
Missing1252
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean0.1061418063
Minimum0
Maximum1
Zeros60878
Zeros (%)87.8%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.916410image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.308021292
Coefficient of variation (CV)2.901978992
Kurtosis4.540525532
Mean0.1061418063
Median Absolute Deviation (MAD)0
Skewness2.55741905
Sum7229
Variance0.0948771163
MonotonicityNot monotonic
2022-09-15T16:48:05.944171image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
060878
87.8%
17229
 
10.4%
(Missing)1252
 
1.8%
ValueCountFrequency (%)
060878
87.8%
17229
 
10.4%
ValueCountFrequency (%)
17229
 
10.4%
060878
87.8%

hallucinogen_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.2%
Missing68918
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:05.970786image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum441
Variance0
MonotonicityIncreasing
2022-09-15T16:48:05.995957image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1441
 
0.6%
(Missing)68918
99.4%
ValueCountFrequency (%)
1441
0.6%
ValueCountFrequency (%)
1441
0.6%
Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
False
69324 
True
 
35
ValueCountFrequency (%)
False69324
99.9%
True35
 
0.1%
2022-09-15T16:48:06.025891image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

heroin_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing64553
Missing (%)93.1%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.050346image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4806
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.075556image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14806
 
6.9%
(Missing)64553
93.1%
ValueCountFrequency (%)
14806
6.9%
ValueCountFrequency (%)
14806
6.9%

heroin_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.2%
Missing69274
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.101128image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum85
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.128435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
185
 
0.1%
(Missing)69274
99.9%
ValueCountFrequency (%)
185
0.1%
ValueCountFrequency (%)
185
0.1%

hydrocodol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.155526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:06.181224image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

hydrocodone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.2%
Missing68940
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.206862image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum419
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.233998image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1419
 
0.6%
(Missing)68940
99.4%
ValueCountFrequency (%)
1419
0.6%
ValueCountFrequency (%)
1419
0.6%

hydrocodone_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)12.5%
Missing69351
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.260818image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum8
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.286972image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
18
 
< 0.1%
(Missing)69351
> 99.9%
ValueCountFrequency (%)
18
< 0.1%
ValueCountFrequency (%)
18
< 0.1%

hydromorphone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.0%
Missing69257
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.313292image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum102
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.338602image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1102
 
0.1%
(Missing)69257
99.9%
ValueCountFrequency (%)
1102
0.1%
ValueCountFrequency (%)
1102
0.1%

hydromorphone_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.364321image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:06.390599image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

hypoxia_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing67225
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.416630image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum2134
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.443328image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12134
 
3.1%
(Missing)67225
96.9%
ValueCountFrequency (%)
12134
3.1%
ValueCountFrequency (%)
12134
3.1%

hypoxic_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing67324
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.605970image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum2035
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.633047image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12035
 
2.9%
(Missing)67324
97.1%
ValueCountFrequency (%)
12035
2.9%
ValueCountFrequency (%)
12035
2.9%

hypoxic_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)16.7%
Missing69353
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.659747image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum6
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.685852image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
16
 
< 0.1%
(Missing)69353
> 99.9%
ValueCountFrequency (%)
16
< 0.1%
ValueCountFrequency (%)
16
< 0.1%

incident_city
Categorical

HIGH CARDINALITY
MISSING

Distinct429
Distinct (%)0.6%
Missing1669
Missing (%)2.4%
Memory size542.0 KiB
CHICAGO
40554 
DES PLAINES
 
908
OAK LAWN
 
772
CICERO
 
770
ARLINGTON HEIGHTS
 
682
Other values (424)
24004 

Unique

Unique124 ?
Unique (%)0.2%

Sample

1st rowCHICAGO
2nd rowJOLIET
3rd rowCHICAGO
4th rowCHICAGO
5th rowCHICAGO

Common Values

ValueCountFrequency (%)
CHICAGO40554
58.5%
DES PLAINES908
 
1.3%
OAK LAWN772
 
1.1%
CICERO770
 
1.1%
ARLINGTON HEIGHTS682
 
1.0%
HARVEY607
 
0.9%
EVANSTON597
 
0.9%
BERWYN537
 
0.8%
NILES533
 
0.8%
SCHAUMBURG516
 
0.7%
Other values (419)21214
30.6%
(Missing)1669
 
2.4%

incident_date
Categorical

HIGH CARDINALITY
MISSING

Distinct59289
Distinct (%)87.6%
Missing1658
Missing (%)2.4%
Memory size542.0 KiB
2022-01-11T00:00:00.000
 
36
2020-05-04T00:00:00.000
 
34
2020-04-16T00:00:00.000
 
34
2020-04-29T00:00:00.000
 
33
2020-04-24T00:00:00.000
 
32
Other values (59284)
67532 

Unique

Unique55882 ?
Unique (%)82.5%

Sample

1st row2020-05-15T18:00:00.000
2nd row2021-04-06T08:00:00.000
3rd row2014-09-21T10:00:00.000
4th row2014-09-22T16:40:00.000
5th row2014-09-27T16:58:00.000

Common Values

ValueCountFrequency (%)
2022-01-11T00:00:00.00036
 
0.1%
2020-05-04T00:00:00.00034
 
< 0.1%
2020-04-16T00:00:00.00034
 
< 0.1%
2020-04-29T00:00:00.00033
 
< 0.1%
2020-04-24T00:00:00.00032
 
< 0.1%
2020-04-19T00:00:00.00032
 
< 0.1%
2020-05-05T00:00:00.00032
 
< 0.1%
2020-04-20T00:00:00.00032
 
< 0.1%
2020-04-23T00:00:00.00030
 
< 0.1%
2020-12-14T00:00:00.00029
 
< 0.1%
Other values (59279)67377
97.1%
(Missing)1658
 
2.4%

incident_street
Categorical

HIGH CARDINALITY
MISSING

Distinct65442
Distinct (%)95.7%
Missing991
Missing (%)1.4%
Memory size542.0 KiB
Unknown
 
175
UNKNOWN
 
131
unknown
 
29
UNKNOWN LOCATION
 
24
UNKNOWN INCIDENT LOCATION
 
23
Other values (65437)
67986 

Unique

Unique63904 ?
Unique (%)93.5%

Sample

1st rowO'Hare, 10000 W. O'Hare Avenue
2nd row424 S HEBBARD
3rd row499 E. North Water St.
4th row1317 PORTLAND
5th row8759 PELIKIN

Common Values

ValueCountFrequency (%)
Unknown175
 
0.3%
UNKNOWN131
 
0.2%
unknown29
 
< 0.1%
UNKNOWN LOCATION24
 
< 0.1%
UNKNOWN INCIDENT LOCATION23
 
< 0.1%
UNK13
 
< 0.1%
10000 W O'Hare Ave12
 
< 0.1%
Unknown at this time12
 
< 0.1%
1511 GREENWOOD RD11
 
< 0.1%
6300 W 95TH ST11
 
< 0.1%
Other values (65432)67927
97.9%
(Missing)991
 
1.4%

incident_zip
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1640
Missing (%)2.4%
Memory size542.0 KiB

inhalant_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.715711image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.742933image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

inhalant_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.769622image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.796414image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

ischemic_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.3%
Missing69316
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.822459image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum43
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.848476image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
143
 
0.1%
(Missing)69316
99.9%
ValueCountFrequency (%)
143
0.1%
ValueCountFrequency (%)
143
0.1%

ischemic_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.6%
Missing69298
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.874246image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum61
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.900555image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
161
 
0.1%
(Missing)69298
99.9%
ValueCountFrequency (%)
161
0.1%
ValueCountFrequency (%)
161
0.1%

isotonitazene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.2%
Missing69313
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.926788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum46
Variance0
MonotonicityIncreasing
2022-09-15T16:48:06.952813image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
146
 
0.1%
(Missing)69313
99.9%
ValueCountFrequency (%)
146
0.1%
ValueCountFrequency (%)
146
0.1%

ketamine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)5.9%
Missing69342
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:06.978185image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum17
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.004887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
117
 
< 0.1%
(Missing)69342
> 99.9%
ValueCountFrequency (%)
117
< 0.1%
ValueCountFrequency (%)
117
< 0.1%

ketamine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.030899image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.057979image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

latino
Boolean

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size67.9 KiB
False
60400 
True
8959 
ValueCountFrequency (%)
False60400
87.1%
True8959
 
12.9%
2022-09-15T16:48:07.089352image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

latitude
Real number (ℝ≥0)

MISSING

Distinct48233
Distinct (%)79.8%
Missing8898
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean41.84373881
Minimum41.46973204
Maximum42.1537467
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.122319image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.46973204
5-th percentile41.59810861
Q141.75042325
median41.85861804
Q341.94091671
95-th percentile42.06083865
Maximum42.1537467
Range0.68401466
Interquartile range (IQR)0.19049346

Descriptive statistics

Standard deviation0.1395350085
Coefficient of variation (CV)0.003334668758
Kurtosis-0.3077776659
Mean41.84373881
Median Absolute Deviation (MAD)0.09884143
Skewness-0.2350669259
Sum2529914.292
Variance0.0194700186
MonotonicityNot monotonic
2022-09-15T16:48:07.163873image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.9574594757
 
0.1%
41.759204156
 
0.1%
42.0021011748
 
0.1%
41.880972646
 
0.1%
42.0579221945
 
0.1%
41.8062548643
 
0.1%
41.7356224242
 
0.1%
41.9998221142
 
0.1%
41.9749509240
 
0.1%
41.7208531240
 
0.1%
Other values (48223)60002
86.5%
(Missing)8898
 
12.8%
ValueCountFrequency (%)
41.469732041
< 0.1%
41.46992581
< 0.1%
41.470013691
< 0.1%
41.470087691
< 0.1%
41.470102481
< 0.1%
ValueCountFrequency (%)
42.15374671
< 0.1%
42.15372961
< 0.1%
42.153670611
< 0.1%
42.153461461
< 0.1%
42.153431081
< 0.1%

levorphanol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.195444image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:07.221178image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

location
Categorical

HIGH CARDINALITY
MISSING

Distinct48260
Distinct (%)79.8%
Missing8898
Missing (%)12.8%
Memory size542.0 KiB
{'type': 'Point', 'coordinates': [-87.80313799, 41.95745947]}
 
57
{'type': 'Point', 'coordinates': [-87.5597331, 41.7592041]}
 
56
{'type': 'Point', 'coordinates': [-87.79169379, 42.00210117]}
 
48
{'type': 'Point', 'coordinates': [-87.66823054, 41.8809726]}
 
46
{'type': 'Point', 'coordinates': [-87.83913756, 42.05792219]}
 
45
Other values (48255)
60209 

Unique

Unique43712 ?
Unique (%)72.3%

Sample

1st row{'type': 'Point', 'coordinates': [-87.61545112, 41.88947682]}
2nd row{'type': 'Point', 'coordinates': [-87.62322044, 41.50733584]}
3rd row{'type': 'Point', 'coordinates': [-87.84976596999999, 41.77362004]}
4th row{'type': 'Point', 'coordinates': [-87.6432531, 41.75286378]}
5th row{'type': 'Point', 'coordinates': [-87.63151396, 41.68470668]}

Common Values

ValueCountFrequency (%)
{'type': 'Point', 'coordinates': [-87.80313799, 41.95745947]}57
 
0.1%
{'type': 'Point', 'coordinates': [-87.5597331, 41.7592041]}56
 
0.1%
{'type': 'Point', 'coordinates': [-87.79169379, 42.00210117]}48
 
0.1%
{'type': 'Point', 'coordinates': [-87.66823054, 41.8809726]}46
 
0.1%
{'type': 'Point', 'coordinates': [-87.83913756, 42.05792219]}45
 
0.1%
{'type': 'Point', 'coordinates': [-87.68314932, 41.80625486]}43
 
0.1%
{'type': 'Point', 'coordinates': [-88.05709437, 41.99982211]}42
 
0.1%
{'type': 'Point', 'coordinates': [-87.69652877, 41.73562242]}42
 
0.1%
{'type': 'Point', 'coordinates': [-87.77818345, 41.72085312]}40
 
0.1%
{'type': 'Point', 'coordinates': [-87.72654538, 41.97495092]}40
 
0.1%
Other values (48250)60002
86.5%
(Missing)8898
 
12.8%

location_address
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing69359
Missing (%)100.0%
Memory size542.0 KiB

location_city
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing69359
Missing (%)100.0%
Memory size542.0 KiB

location_state
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing69359
Missing (%)100.0%
Memory size542.0 KiB

location_zip
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing69359
Missing (%)100.0%
Memory size542.0 KiB

longitude
Real number (ℝ)

MISSING

Distinct48219
Distinct (%)79.8%
Missing8898
Missing (%)12.8%
Infinite0
Infinite (%)0.0%
Mean-87.72745762
Minimum-88.26317794
Maximum-87.52483482
Zeros0
Zeros (%)0.0%
Negative60461
Negative (%)87.2%
Memory size542.0 KiB
2022-09-15T16:48:07.258475image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-88.26317794
5-th percentile-87.96370594
Q1-87.77762076
median-87.70680262
Q3-87.64927302
95-th percentile-87.58031554
Maximum-87.52483482
Range0.73834312
Interquartile range (IQR)0.12834774

Descriptive statistics

Standard deviation0.1163484499
Coefficient of variation (CV)-0.001326248965
Kurtosis2.741660551
Mean-87.72745762
Median Absolute Deviation (MAD)0.06295688
Skewness-1.393902633
Sum-5304089.815
Variance0.01353696179
MonotonicityNot monotonic
2022-09-15T16:48:07.300172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.8031379957
 
0.1%
-87.559733156
 
0.1%
-87.7916937948
 
0.1%
-87.6682305446
 
0.1%
-87.8391375645
 
0.1%
-87.6831493243
 
0.1%
-87.6965287742
 
0.1%
-88.0570943742
 
0.1%
-87.7265453840
 
0.1%
-87.7781834540
 
0.1%
Other values (48209)60002
86.5%
(Missing)8898
 
12.8%
ValueCountFrequency (%)
-88.263177941
< 0.1%
-88.263148671
< 0.1%
-88.26280711
< 0.1%
-88.262507261
< 0.1%
-88.262181351
< 0.1%
ValueCountFrequency (%)
-87.524834821
< 0.1%
-87.524901341
< 0.1%
-87.524905011
< 0.1%
-87.525321621
< 0.1%
-87.525510461
< 0.1%

lorazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.7%
Missing69213
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.332143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum146
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.358871image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1146
 
0.2%
(Missing)69213
99.8%
ValueCountFrequency (%)
1146
0.2%
ValueCountFrequency (%)
1146
0.2%

lorazepam_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.384807image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:07.410369image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

lsd_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)20.0%
Missing69354
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.436113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.462152image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15
 
< 0.1%
(Missing)69354
> 99.9%
ValueCountFrequency (%)
15
< 0.1%
ValueCountFrequency (%)
15
< 0.1%

lsd_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.487556image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:07.513117image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

lysergic_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)16.7%
Missing69353
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.538658image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum6
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.565167image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
16
 
< 0.1%
(Missing)69353
> 99.9%
ValueCountFrequency (%)
16
< 0.1%
ValueCountFrequency (%)
16
< 0.1%

lysergic_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.590827image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:07.616769image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

manner
Categorical

Distinct6
Distinct (%)< 0.1%
Missing492
Missing (%)0.7%
Memory size542.0 KiB
NATURAL
35398 
ACCIDENT
20988 
HOMICIDE
6752 
SUICIDE
3816 
UNDETERMINED
 
1153

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPENDING
2nd rowPENDING
3rd rowUNDETERMINED
4th rowNATURAL
5th rowNATURAL

Common Values

ValueCountFrequency (%)
NATURAL35398
51.0%
ACCIDENT20988
30.3%
HOMICIDE6752
 
9.7%
SUICIDE3816
 
5.5%
UNDETERMINED1153
 
1.7%
PENDING760
 
1.1%
(Missing)492
 
0.7%

Category Frequency Plot

2022-09-15T16:48:07.651392image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

mda_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)6.7%
Missing69344
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.679788image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum15
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.711442image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
115
 
< 0.1%
(Missing)69344
> 99.9%
ValueCountFrequency (%)
115
< 0.1%
ValueCountFrequency (%)
115
< 0.1%

mdma_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.2%
Missing69274
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.737588image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum85
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.764638image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
185
 
0.1%
(Missing)69274
99.9%
ValueCountFrequency (%)
185
0.1%
ValueCountFrequency (%)
185
0.1%

mdma_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)33.3%
Missing69356
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.790873image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.817526image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13
 
< 0.1%
(Missing)69356
> 99.9%
ValueCountFrequency (%)
13
< 0.1%
ValueCountFrequency (%)
13
< 0.1%

meperidine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.843505image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:07.869128image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

metaxalone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)33.3%
Missing69356
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.894719image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.922601image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13
 
< 0.1%
(Missing)69356
> 99.9%
ValueCountFrequency (%)
13
< 0.1%
ValueCountFrequency (%)
13
< 0.1%

methadone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.1%
Missing68629
Missing (%)98.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:07.949432image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum730
Variance0
MonotonicityIncreasing
2022-09-15T16:48:07.977310image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1730
 
1.1%
(Missing)68629
98.9%
ValueCountFrequency (%)
1730
1.1%
ValueCountFrequency (%)
1730
1.1%

methadone_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)3.7%
Missing69332
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.003673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum27
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.029208image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
127
 
< 0.1%
(Missing)69332
> 99.9%
ValueCountFrequency (%)
127
< 0.1%
ValueCountFrequency (%)
127
< 0.1%

methamphetamine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.3%
Missing69030
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.054806image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum329
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.080810image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1329
 
0.5%
(Missing)69030
99.5%
ValueCountFrequency (%)
1329
0.5%
ValueCountFrequency (%)
1329
0.5%

methamphetamine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.0%
Missing69334
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.107968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum25
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.133677image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
125
 
< 0.1%
(Missing)69334
> 99.9%
ValueCountFrequency (%)
125
< 0.1%
ValueCountFrequency (%)
125
< 0.1%

methocarbamol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)14.3%
Missing69352
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.159048image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum7
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.366763image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
17
 
< 0.1%
(Missing)69352
> 99.9%
ValueCountFrequency (%)
17
< 0.1%
ValueCountFrequency (%)
17
< 0.1%

methorphan_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)8.3%
Missing69347
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.392988image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum12
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.419571image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
112
 
< 0.1%
(Missing)69347
> 99.9%
ValueCountFrequency (%)
112
< 0.1%
ValueCountFrequency (%)
112
< 0.1%

methorphan_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.445077image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:08.470876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

methoxyacetyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)3.7%
Missing69332
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.496299image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum27
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.522260image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
127
 
< 0.1%
(Missing)69332
> 99.9%
ValueCountFrequency (%)
127
< 0.1%
ValueCountFrequency (%)
127
< 0.1%

methylenedioxymethamphetamine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.8%
Missing69240
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.548287image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum119
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.574717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1119
 
0.2%
(Missing)69240
99.8%
ValueCountFrequency (%)
1119
0.2%
ValueCountFrequency (%)
1119
0.2%

methylenedioxymethamphetamine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)16.7%
Missing69353
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.600416image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum6
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.626329image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
16
 
< 0.1%
(Missing)69353
> 99.9%
ValueCountFrequency (%)
16
< 0.1%
ValueCountFrequency (%)
16
< 0.1%

methylphenidate_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)20.0%
Missing69354
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.652228image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.678441image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15
 
< 0.1%
(Missing)69354
> 99.9%
ValueCountFrequency (%)
15
< 0.1%
ValueCountFrequency (%)
15
< 0.1%

metonitazene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)1.3%
Missing69281
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.704127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum78
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.731122image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
178
 
0.1%
(Missing)69281
99.9%
ValueCountFrequency (%)
178
0.1%
ValueCountFrequency (%)
178
0.1%

mitragynine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.9%
Missing69249
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.757389image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum110
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.783163image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1110
 
0.2%
(Missing)69249
99.8%
ValueCountFrequency (%)
1110
0.2%
ValueCountFrequency (%)
1110
0.2%

mitragynine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.809214image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.836497image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

morphine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.5%
Missing69167
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.863324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum192
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.890530image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1192
 
0.3%
(Missing)69167
99.7%
ValueCountFrequency (%)
1192
0.3%
ValueCountFrequency (%)
1192
0.3%

morphine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)16.7%
Missing69353
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.917145image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum6
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.943054image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
16
 
< 0.1%
(Missing)69353
> 99.9%
ValueCountFrequency (%)
16
< 0.1%
ValueCountFrequency (%)
16
< 0.1%

nitazene_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.8%
Missing69236
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:08.968611image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum123
Variance0
MonotonicityIncreasing
2022-09-15T16:48:08.994704image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1123
 
0.2%
(Missing)69236
99.8%
ValueCountFrequency (%)
1123
0.2%
ValueCountFrequency (%)
1123
0.2%

nonfentanyl_opioid_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing62554
Missing (%)90.2%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.020745image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum6805
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.047200image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
16805
 
9.8%
(Missing)62554
90.2%
ValueCountFrequency (%)
16805
9.8%
ValueCountFrequency (%)
16805
9.8%

norfentanyl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.5%
Missing69337
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.073777image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum22
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.098912image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
122
 
< 0.1%
(Missing)69337
> 99.9%
ValueCountFrequency (%)
122
< 0.1%
ValueCountFrequency (%)
122
< 0.1%

objectid
Real number (ℝ≥0)

UNIQUE

Distinct69359
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean34693.38939
Minimum1
Maximum69428
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.137673image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3468.9
Q117340.5
median34680
Q352022.5
95-th percentile65960.1
Maximum69428
Range69427
Interquartile range (IQR)34682

Descriptive statistics

Standard deviation20040.88197
Coefficient of variation (CV)0.5776570789
Kurtosis-1.199063138
Mean34693.38939
Median Absolute Deviation (MAD)17341
Skewness0.001925933272
Sum2406298795
Variance401636950.3
MonotonicityNot monotonic
2022-09-15T16:48:09.179625image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
384791
 
< 0.1%
462451
 
< 0.1%
462311
 
< 0.1%
462321
 
< 0.1%
462331
 
< 0.1%
462341
 
< 0.1%
462351
 
< 0.1%
462361
 
< 0.1%
462371
 
< 0.1%
462381
 
< 0.1%
Other values (69349)69349
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
21
< 0.1%
31
< 0.1%
41
< 0.1%
51
< 0.1%
ValueCountFrequency (%)
694281
< 0.1%
694271
< 0.1%
694261
< 0.1%
694251
< 0.1%
694241
< 0.1%

opiate_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69083
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.211909image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum276
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.237750image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1276
 
0.4%
(Missing)69083
99.6%
ValueCountFrequency (%)
1276
0.4%
ValueCountFrequency (%)
1276
0.4%

opiate_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)5.6%
Missing69341
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.263319image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum18
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.289984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
118
 
< 0.1%
(Missing)69341
> 99.9%
ValueCountFrequency (%)
118
< 0.1%
ValueCountFrequency (%)
118
< 0.1%

opiate_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing59194
Missing (%)85.3%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.316592image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum10165
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.342271image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
110165
 
14.7%
(Missing)59194
85.3%
ValueCountFrequency (%)
110165
14.7%
ValueCountFrequency (%)
110165
14.7%

opioid_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.2%
Missing68952
Missing (%)99.4%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.368051image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum407
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.395134image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1407
 
0.6%
(Missing)68952
99.4%
ValueCountFrequency (%)
1407
0.6%
ValueCountFrequency (%)
1407
0.6%

opioid_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)8.3%
Missing69347
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.421423image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum12
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.447764image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
112
 
< 0.1%
(Missing)69347
> 99.9%
ValueCountFrequency (%)
112
< 0.1%
ValueCountFrequency (%)
112
< 0.1%

opioids
Real number (ℝ≥0)

MISSING
ZEROS

Distinct2
Distinct (%)< 0.1%
Missing1252
Missing (%)1.8%
Infinite0
Infinite (%)0.0%
Mean0.1534790844
Minimum0
Maximum1
Zeros57654
Zeros (%)83.1%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.473641image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.3604513319
Coefficient of variation (CV)2.348537153
Kurtosis1.697064178
Mean0.1534790844
Median Absolute Deviation (MAD)0
Skewness1.922762165
Sum10453
Variance0.1299251627
MonotonicityNot monotonic
2022-09-15T16:48:09.501278image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
057654
83.1%
110453
 
15.1%
(Missing)1252
 
1.8%
ValueCountFrequency (%)
057654
83.1%
110453
 
15.1%
ValueCountFrequency (%)
110453
 
15.1%
057654
83.1%

oxazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)6.2%
Missing69343
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.528298image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum16
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.554866image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
116
 
< 0.1%
(Missing)69343
> 99.9%
ValueCountFrequency (%)
116
< 0.1%
ValueCountFrequency (%)
116
< 0.1%

oxycodone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.6%
Missing69190
Missing (%)99.8%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.581588image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum169
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.608398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1169
 
0.2%
(Missing)69190
99.8%
ValueCountFrequency (%)
1169
0.2%
ValueCountFrequency (%)
1169
0.2%

oxycodone_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)12.5%
Missing69351
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.634674image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum8
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.661222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
18
 
< 0.1%
(Missing)69351
> 99.9%
ValueCountFrequency (%)
18
< 0.1%
ValueCountFrequency (%)
18
< 0.1%

oxymorphone_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)3.0%
Missing69326
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.687795image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum33
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.713831image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
133
 
< 0.1%
(Missing)69326
> 99.9%
ValueCountFrequency (%)
133
< 0.1%
ValueCountFrequency (%)
133
< 0.1%

oxymorphone_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.739426image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:09.765461image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

para-fluorobutyryl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)9.1%
Missing69348
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.791906image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum11
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.817669image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
111
 
< 0.1%
(Missing)69348
> 99.9%
ValueCountFrequency (%)
111
< 0.1%
ValueCountFrequency (%)
111
< 0.1%

pcp_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)9.1%
Missing69348
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.843042image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum11
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.868686image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
111
 
< 0.1%
(Missing)69348
> 99.9%
ValueCountFrequency (%)
111
< 0.1%
ValueCountFrequency (%)
111
< 0.1%

pcp_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)33.3%
Missing69356
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.894876image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum3
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.920961image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
13
 
< 0.1%
(Missing)69356
> 99.9%
ValueCountFrequency (%)
13
< 0.1%
ValueCountFrequency (%)
13
< 0.1%

phencyclidine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69103
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.946856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum256
Variance0
MonotonicityIncreasing
2022-09-15T16:48:09.973545image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1256
 
0.4%
(Missing)69103
99.6%
ValueCountFrequency (%)
1256
0.4%
ValueCountFrequency (%)
1256
0.4%

phencyclidine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.2%
Missing69335
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:09.999482image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum24
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.025483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
124
 
< 0.1%
(Missing)69335
> 99.9%
ValueCountFrequency (%)
124
< 0.1%
ValueCountFrequency (%)
124
< 0.1%

phentermine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)14.3%
Missing69352
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.051303image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum7
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.077937image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
17
 
< 0.1%
(Missing)69352
> 99.9%
ValueCountFrequency (%)
17
< 0.1%
ValueCountFrequency (%)
17
< 0.1%

polysubstance_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)20.0%
Missing69354
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.103802image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.129771image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15
 
< 0.1%
(Missing)69354
> 99.9%
ValueCountFrequency (%)
15
< 0.1%
ValueCountFrequency (%)
15
< 0.1%

polysubstance_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)5.6%
Missing69341
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.155055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum18
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.181736image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
118
 
< 0.1%
(Missing)69341
> 99.9%
ValueCountFrequency (%)
118
< 0.1%
ValueCountFrequency (%)
118
< 0.1%

polysubstance_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)4.3%
Missing69336
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.208125image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum23
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.233263image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
123
 
< 0.1%
(Missing)69336
> 99.9%
ValueCountFrequency (%)
123
< 0.1%
ValueCountFrequency (%)
123
< 0.1%

primary_cod
Categorical

HIGH CARDINALITY
MISSING

Distinct13692
Distinct (%)20.0%
Missing815
Missing (%)1.2%
Memory size542.0 KiB
ORGANIC CARDIOVASCULAR DISEASE
6316 
PNEUMONIA NOVEL CORONA (COVID-19) VIRAL INFECTION
 
4119
MULTIPLE GUNSHOT WOUNDS
 
3416
HYPERTENSIVE CARDIOVASCULAR DISEASE
 
2772
NOVEL CORONA (COVID-19) VIRAL INFECTION
 
2525
Other values (13687)
49396 

Unique

Unique11011 ?
Unique (%)16.1%

Sample

1st rowDROWNING
2nd rowHYPERTENSIVE ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE
3rd rowDIABETIC KETOACIDOSIS
4th rowHYPERTENSIVE AND ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE
5th rowHYPERTENSIVE AND ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE

Common Values

ValueCountFrequency (%)
ORGANIC CARDIOVASCULAR DISEASE6316
 
9.1%
PNEUMONIA NOVEL CORONA (COVID-19) VIRAL INFECTION4119
 
5.9%
MULTIPLE GUNSHOT WOUNDS3416
 
4.9%
HYPERTENSIVE CARDIOVASCULAR DISEASE2772
 
4.0%
NOVEL CORONA (COVID-19) VIRAL INFECTION2525
 
3.6%
HYPERTENSIVE ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE1534
 
2.2%
ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE1226
 
1.8%
PNEUMONIA NOVEL CORONA (COVID-19) VIRUS INFECTION969
 
1.4%
GUNSHOT WOUND OF HEAD943
 
1.4%
CHRONIC ETHANOLISM824
 
1.2%
Other values (13682)43900
63.3%

primarycause
Categorical

HIGH CARDINALITY
MISSING

Distinct9901
Distinct (%)14.4%
Missing815
Missing (%)1.2%
Memory size542.0 KiB
ORGANIC CARDIOVASCULAR DISEASE
6340 
PNEUMONIA
5147 
MULTIPLE GUNSHOT WOUNDS
 
3422
HYPERTENSIVE CARDIOVASCULAR DISEASE
 
2797
NOVEL CORONA (COVID-19) VIRAL INFECTION
 
2532
Other values (9896)
48306 

Unique

Unique7773 ?
Unique (%)11.3%

Sample

1st rowDROWNING
2nd rowHYPERTENSIVE ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE
3rd rowDIABETIC KETOACIDOSIS
4th rowHYPERTENSIVE AND ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE
5th rowHYPERTENSIVE AND ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE

Common Values

ValueCountFrequency (%)
ORGANIC CARDIOVASCULAR DISEASE6340
 
9.1%
PNEUMONIA5147
 
7.4%
MULTIPLE GUNSHOT WOUNDS3422
 
4.9%
HYPERTENSIVE CARDIOVASCULAR DISEASE2797
 
4.0%
NOVEL CORONA (COVID-19) VIRAL INFECTION2532
 
3.7%
MULTIPLE INJURIES2254
 
3.2%
ACUTE HYPOXIC RESPIRATORY FAILURE1841
 
2.7%
HYPERTENSIVE ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE1543
 
2.2%
ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE1235
 
1.8%
GUNSHOT WOUND OF HEAD947
 
1.4%
Other values (9891)40486
58.4%

primarycause_linea
Categorical

HIGH CARDINALITY
MISSING

Distinct2771
Distinct (%)12.3%
Missing46767
Missing (%)67.4%
Memory size542.0 KiB
NOVEL CORONA (COVID-19) VIRAL INFECTION
5918 
PNEUMONIA
2387 
FALL
1959 
NOVEL CORONA (COVID-19) VIRUS INFECTION
1873 
MOTOR VEHICLE COLLISION
 
736
Other values (2766)
9719 

Unique

Unique2166 ?
Unique (%)9.6%

Sample

1st rowRUPTURE OF ARTERIOVENOUS FISTULA
2nd rowFAILED DIALYSIS ARTERIOVENOUS FISTULA
3rd rowPEDESTRIAN STRUCK BY CAR
4th rowCHRONIC ALCOHOLISM
5th rowUNDETERMINED NATURAL CAUSES

Common Values

ValueCountFrequency (%)
NOVEL CORONA (COVID-19) VIRAL INFECTION5918
 
8.5%
PNEUMONIA2387
 
3.4%
FALL1959
 
2.8%
NOVEL CORONA (COVID-19) VIRUS INFECTION1873
 
2.7%
MOTOR VEHICLE COLLISION736
 
1.1%
HANGING438
 
0.6%
MOTOR VEHICLE STRIKING PEDESTRIAN406
 
0.6%
FALL FROM HEIGHT258
 
0.4%
FALL DOWN STAIRS234
 
0.3%
MOTOR VEHICLE STRIKING FIXED OBJECT226
 
0.3%
Other values (2761)8157
 
11.8%
(Missing)46767
67.4%

primarycause_lineb
Categorical

HIGH CARDINALITY
MISSING

Distinct399
Distinct (%)12.3%
Missing66113
Missing (%)95.3%
Memory size542.0 KiB
NOVEL CORONA (COVID-19) VIRAL INFECTION
2058 
NOVEL CORONA (COVID-19) VIRUS INFECTION
381 
HYPERTENSIVE CARDIOVASCULAR DISEASE
 
71
HOUSE FIRE
 
49
.
 
40
Other values (394)
647 

Unique

Unique324 ?
Unique (%)10.0%

Sample

1st rowCHRONIC RENAL FAILURE
2nd rowHYPERTENSIVE CARDIOVASCULAR DISEASE
3rd rowMOTOR VEHICLE STRIKING PARKED CARS
4th rowSEPTIC EMBOLI
5th row.

Common Values

ValueCountFrequency (%)
NOVEL CORONA (COVID-19) VIRAL INFECTION2058
 
3.0%
NOVEL CORONA (COVID-19) VIRUS INFECTION381
 
0.5%
HYPERTENSIVE CARDIOVASCULAR DISEASE71
 
0.1%
HOUSE FIRE49
 
0.1%
.40
 
0.1%
HYPERTENSIVE AND ATHEROSCLEROTIC CARDIOVASCULAR DISEASE37
 
0.1%
FALL24
 
< 0.1%
CHRONIC ETHANOLISM18
 
< 0.1%
CARELESS USE OF SMOKING MATERIALS17
 
< 0.1%
APARTMENT FIRE15
 
< 0.1%
Other values (389)536
 
0.8%
(Missing)66113
95.3%

primarycause_linec
Categorical

MISSING

Distinct9
Distinct (%)12.5%
Missing69287
Missing (%)99.9%
Memory size542.0 KiB
.
63 
END STAGE RENAL DISEASE
 
2
HEPATITIS C
 
1
HIGH BLOOD PRESSURE
 
1
..
 
1
Other values (4)
 
4

Unique

Unique7 ?
Unique (%)9.7%

Sample

1st rowHEPATITIS C
2nd row.
3rd row.
4th row.
5th row.

Common Values

ValueCountFrequency (%)
.63
 
0.1%
END STAGE RENAL DISEASE2
 
< 0.1%
HEPATITIS C1
 
< 0.1%
HIGH BLOOD PRESSURE1
 
< 0.1%
..1
 
< 0.1%
HYPERTENSIVE CARDIOVASCULAR DISEASE1
 
< 0.1%
HYPERTENSION, DIABETES MELLITUS, AND CORONARY ARTERY DISEASE1
 
< 0.1%
CHRONIC ETHANOLISM, DIABETES MELLITUS1
 
< 0.1%
DIABETES MELLITUS1
 
< 0.1%
(Missing)69287
99.9%

Category Frequency Plot

2022-09-15T16:48:10.273183image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

propoxyphene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.304464image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:10.565547image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

race
Categorical

Distinct6
Distinct (%)< 0.1%
Missing384
Missing (%)0.6%
Memory size542.0 KiB
White
37824 
Black
28336 
Asian
 
1580
Other
 
906
Unknown
 
270

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowWhite
2nd rowWhite
3rd rowBlack
4th rowBlack
5th rowWhite

Common Values

ValueCountFrequency (%)
White37824
54.5%
Black28336
40.9%
Asian1580
 
2.3%
Other906
 
1.3%
Unknown270
 
0.4%
Am. Indian59
 
0.1%
(Missing)384
 
0.6%

Category Frequency Plot

2022-09-15T16:48:10.600022image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

residence_city
Categorical

HIGH CARDINALITY
MISSING

Distinct1211
Distinct (%)1.8%
Missing1906
Missing (%)2.7%
Memory size542.0 KiB
Chicago
37483 
Des Plaines
 
914
Oak Lawn
 
808
Cicero
 
773
Arlington Heights
 
642
Other values (1206)
26833 

Unique

Unique643 ?
Unique (%)1.0%

Sample

1st rowJoliet
2nd rowBerwyn
3rd rowBerwyn
4th rowBerwyn
5th rowBlue Island

Common Values

ValueCountFrequency (%)
Chicago37483
54.0%
Des Plaines914
 
1.3%
Oak Lawn808
 
1.2%
Cicero773
 
1.1%
Arlington Heights642
 
0.9%
Berwyn614
 
0.9%
Evanston573
 
0.8%
Orland Park534
 
0.8%
Skokie525
 
0.8%
Niles512
 
0.7%
Other values (1201)24075
34.7%
(Missing)1906
 
2.7%

residence_zip
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing1802
Missing (%)2.6%
Memory size542.0 KiB

secondarycause
Categorical

HIGH CARDINALITY
MISSING

Distinct10995
Distinct (%)39.4%
Missing41485
Missing (%)59.8%
Memory size542.0 KiB
DIABETES MELLITUS
 
1698
OBESITY
 
1463
HYPERTENSION
 
1127
CHRONIC ETHANOLISM
 
736
HYPERTENSIVE CARDIOVASCULAR DISEASE
 
661
Other values (10990)
22189 

Unique

Unique9555 ?
Unique (%)34.3%

Sample

1st rowOBESITY
2nd rowCHRONIC ALCOHOLISM
3rd rowBRONCHOPNEUMONIA
4th rowCHRONIC ALCOHOLISM
5th rowHYPERTENSIVE AND ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE

Common Values

ValueCountFrequency (%)
DIABETES MELLITUS1698
 
2.4%
OBESITY1463
 
2.1%
HYPERTENSION1127
 
1.6%
CHRONIC ETHANOLISM736
 
1.1%
HYPERTENSIVE CARDIOVASCULAR DISEASE661
 
1.0%
HYPERTENSION, DIABETES MELLITUS477
 
0.7%
CHRONIC OBSTRUCTIVE PULMONARY DISEASE412
 
0.6%
HYPERTENSIVE ARTERIOSCLEROTIC CARDIOVASCULAR DISEASE362
 
0.5%
DIABETES MELLITUS, HYPERTENSION244
 
0.4%
DIABETES MELLITUS, OBESITY227
 
0.3%
Other values (10985)20467
29.5%
(Missing)41485
59.8%

sedative_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing67194
Missing (%)96.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.628232image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum2165
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.653389image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12165
 
3.1%
(Missing)67194
96.9%
ValueCountFrequency (%)
12165
3.1%
ValueCountFrequency (%)
12165
3.1%

stimulant_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing64025
Missing (%)92.3%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.679110image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum5334
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.704945image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
15334
 
7.7%
(Missing)64025
92.3%
ValueCountFrequency (%)
15334
7.7%
ValueCountFrequency (%)
15334
7.7%

tarpentadol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.730733image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:10.756356image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

temazepam_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.3%
Missing69315
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.782254image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum44
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.807642image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
144
 
0.1%
(Missing)69315
99.9%
ValueCountFrequency (%)
144
0.1%
ValueCountFrequency (%)
144
0.1%

tizanidine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.833390image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:10.859147image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

topiramate_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.4%
Missing69317
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.884662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum42
Variance0
MonotonicityIncreasing
2022-09-15T16:48:10.911822image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
142
 
0.1%
(Missing)69317
99.9%
ValueCountFrequency (%)
142
0.1%
ValueCountFrequency (%)
142
0.1%

topiramate_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.938127image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:10.963500image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

toxic_tag
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.6%
Missing69180
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:10.989435image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum179
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.016334image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1179
 
0.3%
(Missing)69180
99.7%
ValueCountFrequency (%)
1179
0.3%
ValueCountFrequency (%)
1179
0.3%

tramadol_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.3%
Missing69031
Missing (%)99.5%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.042316image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum328
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.068360image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1328
 
0.5%
(Missing)69031
99.5%
ValueCountFrequency (%)
1328
0.5%
ValueCountFrequency (%)
1328
0.5%

tramadol_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.094402image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.121535image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

u-47700_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)2.3%
Missing69316
Missing (%)99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.148428image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum43
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.173528image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
143
 
0.1%
(Missing)69316
99.9%
ValueCountFrequency (%)
143
0.1%
ValueCountFrequency (%)
143
0.1%

u-49900_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)50.0%
Missing69357
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.199397image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum2
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.226398image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
12
 
< 0.1%
(Missing)69357
> 99.9%
ValueCountFrequency (%)
12
< 0.1%
ValueCountFrequency (%)
12
< 0.1%

utonitazene_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)100.0%
Missing69358
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.252941image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviationnan
Coefficient of variation (CV)nan
Kurtosisnan
Mean1
Median Absolute Deviation (MAD)0
Skewnessnan
Sum1
Variancenan
MonotonicityStrictly increasing
2022-09-15T16:48:11.278551image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
11
 
< 0.1%
(Missing)69358
> 99.9%
ValueCountFrequency (%)
11
< 0.1%
ValueCountFrequency (%)
11
< 0.1%

valeryl_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)5.6%
Missing69341
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.304350image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum18
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.330740image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
118
 
< 0.1%
(Missing)69341
> 99.9%
ValueCountFrequency (%)
118
< 0.1%
ValueCountFrequency (%)
118
< 0.1%

xylazine_1
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.3%
Missing69064
Missing (%)99.6%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.357240image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum295
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.382887image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1295
 
0.4%
(Missing)69064
99.6%
ValueCountFrequency (%)
1295
0.4%
ValueCountFrequency (%)
1295
0.4%

xylazine_2
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)25.0%
Missing69355
Missing (%)> 99.9%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.408975image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum4
Variance0
MonotonicityIncreasing
2022-09-15T16:48:11.436155image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
14
 
< 0.1%
(Missing)69355
> 99.9%
ValueCountFrequency (%)
14
< 0.1%
ValueCountFrequency (%)
14
< 0.1%

composite_latitude
Real number (ℝ≥0)

MISSING

Distinct53540
Distinct (%)79.6%
Missing2086
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean41.84263957
Minimum41.40003502
Maximum42.19982043
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.472744image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.40003502
5-th percentile41.58445829
Q141.74850579
median41.85854019
Q341.94573006
95-th percentile42.06595049
Maximum42.19982043
Range0.7997854034
Interquartile range (IQR)0.19722427

Descriptive statistics

Standard deviation0.1453241969
Coefficient of variation (CV)0.003473112557
Kurtosis-0.2495593152
Mean41.84263957
Median Absolute Deviation (MAD)0.1018273
Skewness-0.2622782397
Sum2814879.892
Variance0.02111912221
MonotonicityNot monotonic
2022-09-15T16:48:11.517363image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.9574594757
 
0.1%
41.759204156
 
0.1%
42.0021011748
 
0.1%
41.880972646
 
0.1%
42.0579221945
 
0.1%
41.997574744
 
0.1%
41.8062548643
 
0.1%
41.7356224242
 
0.1%
41.9998221142
 
0.1%
41.9738122440
 
0.1%
Other values (53530)66810
96.3%
(Missing)2086
 
3.0%
ValueCountFrequency (%)
41.400035022
 
< 0.1%
41.401155013
 
< 0.1%
41.40276911
 
< 0.1%
41.4030113214
< 0.1%
41.404675271
 
< 0.1%
ValueCountFrequency (%)
42.199820431
< 0.1%
42.199799081
< 0.1%
42.199537271
< 0.1%
42.199110971
< 0.1%
42.198984991
< 0.1%

composite_longitude
Real number (ℝ)

MISSING

Distinct53527
Distinct (%)79.6%
Missing2086
Missing (%)3.0%
Infinite0
Infinite (%)0.0%
Mean-87.73518955
Minimum-88.29986998
Maximum-87.50000326
Zeros0
Zeros (%)0.0%
Negative67273
Negative (%)97.0%
Memory size542.0 KiB
2022-09-15T16:48:11.559431image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-88.29986998
5-th percentile-88.00128362
Q1-87.78909854
median-87.70977302
Q3-87.64971841
95-th percentile-87.58009888
Maximum-87.50000326
Range0.7998667206
Interquartile range (IQR)0.13938013

Descriptive statistics

Standard deviation0.1271173298
Coefficient of variation (CV)-0.00144887508
Kurtosis2.633210067
Mean-87.73518955
Median Absolute Deviation (MAD)0.06659331
Skewness-1.433390043
Sum-5902209.407
Variance0.01615881553
MonotonicityNot monotonic
2022-09-15T16:48:11.601070image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.8031379957
 
0.1%
-87.559733156
 
0.1%
-87.7916937948
 
0.1%
-87.6682305446
 
0.1%
-87.8391375645
 
0.1%
-87.887646444
 
0.1%
-87.6831493243
 
0.1%
-88.0570943742
 
0.1%
-87.6965287742
 
0.1%
-87.7781834540
 
0.1%
Other values (53517)66810
96.3%
(Missing)2086
 
3.0%
ValueCountFrequency (%)
-88.299869981
 
< 0.1%
-88.299814951
 
< 0.1%
-88.299664951
 
< 0.1%
-88.29954491
 
< 0.1%
-88.299369815
< 0.1%
ValueCountFrequency (%)
-87.500003261
< 0.1%
-87.500029951
< 0.1%
-87.500050311
< 0.1%
-87.500079971
< 0.1%
-87.500114941
< 0.1%

geometry
Categorical

HIGH CARDINALITY

Distinct53589
Distinct (%)77.3%
Missing0
Missing (%)0.0%
Memory size542.0 KiB
POINT EMPTY
 
2086
POINT (-87.80313799 41.95745947)
 
57
POINT (-87.5597331 41.7592041)
 
56
POINT (-87.79169379 42.00210117)
 
48
POINT (-87.66823054 41.8809726)
 
46
Other values (53584)
67066 

Unique

Unique48367 ?
Unique (%)69.7%

Sample

1st rowPOINT (-87.88024957384711 41.97857076731047)
2nd rowPOINT (-88.04523527996852 41.51683075424138)
3rd rowPOINT (-87.61545112 41.88947682)
4th rowPOINT (-87.62322044 41.50733584)
5th rowPOINT (-87.84976596999999 41.77362004)

Common Values

ValueCountFrequency (%)
POINT EMPTY2086
 
3.0%
POINT (-87.80313799 41.95745947)57
 
0.1%
POINT (-87.5597331 41.7592041)56
 
0.1%
POINT (-87.79169379 42.00210117)48
 
0.1%
POINT (-87.66823054 41.8809726)46
 
0.1%
POINT (-87.83913756 42.05792219)45
 
0.1%
POINT (-87.88764639999994 41.99757470000003)44
 
0.1%
POINT (-87.68314932 41.80625486)43
 
0.1%
POINT (-88.05709437 41.99982211)42
 
0.1%
POINT (-87.69652877 41.73562242)42
 
0.1%
Other values (53579)66850
96.4%

OBJECTID_left
Real number (ℝ≥0)

MISSING

Distinct156
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean4835.13514
Minimum2
Maximum70606
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.644920image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile130
Q1713
median3361
Q33361
95-th percentile10445
Maximum70606
Range70604
Interquartile range (IQR)2648

Descriptive statistics

Standard deviation11427.89862
Coefficient of variation (CV)2.363511731
Kurtosis24.08452142
Mean4835.13514
Median Absolute Deviation (MAD)0
Skewness4.988271231
Sum316677176
Variance130596867
MonotonicityNot monotonic
2022-09-15T16:48:11.686690image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
336140833
58.9%
625762
 
1.1%
132760
 
1.1%
2779671
 
1.0%
428646
 
0.9%
10430590
 
0.9%
11670579
 
0.8%
392536
 
0.8%
547532
 
0.8%
716531
 
0.8%
Other values (146)19055
27.5%
(Missing)3864
 
5.6%
ValueCountFrequency (%)
271
 
0.1%
47
 
< 0.1%
7191
0.3%
822
 
< 0.1%
13214
0.3%
ValueCountFrequency (%)
7060628
< 0.1%
7052326
< 0.1%
7050554
0.1%
7037624
< 0.1%
7036714
 
< 0.1%

AGENCY
Real number (ℝ≥0)

MISSING

Distinct128
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean7959.436858
Minimum1
Maximum10010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.728510image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4070
Q14980
median10010
Q310010
95-th percentile10010
Maximum10010
Range10009
Interquartile range (IQR)5030

Descriptive statistics

Standard deviation2796.292113
Coefficient of variation (CV)0.3513178336
Kurtosis-0.3942359741
Mean7959.436858
Median Absolute Deviation (MAD)0
Skewness-0.9031018416
Sum521303317
Variance7819249.584
MonotonicityNot monotonic
2022-09-15T16:48:11.770318image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1001040833
58.9%
11107
 
1.6%
150762
 
1.1%
4690760
 
1.1%
5540671
 
1.0%
4010646
 
0.9%
5570590
 
0.9%
5560579
 
0.8%
5500536
 
0.8%
4630532
 
0.8%
Other values (118)18479
26.6%
(Missing)3864
 
5.6%
ValueCountFrequency (%)
11107
1.6%
150762
1.1%
4000220
 
0.3%
4010646
0.9%
402029
 
< 0.1%
ValueCountFrequency (%)
1001040833
58.9%
9999350
 
0.5%
5700104
 
0.1%
5690265
 
0.4%
5680306
 
0.4%

AGENCY_DESC
Categorical

HIGH CARDINALITY
MISSING

Distinct155
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Memory size542.0 KiB
CITY OF CHICAGO
40833 
CITY OF CICERO
 
762
VILLAGE OF OAK LAWN
 
760
CITY OF DES PLAINES
 
671
VILLAGE OF ARLINGTON HEIGHTS
 
646
Other values (150)
21823 

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st rowCITY OF CHICAGO
2nd rowCITY OF CHICAGO
3rd rowCITY OF CHICAGO HEIGHTS
4th rowVILLAGE OF HODGKINS
5th rowCITY OF CHICAGO

Common Values

ValueCountFrequency (%)
CITY OF CHICAGO40833
58.9%
CITY OF CICERO762
 
1.1%
VILLAGE OF OAK LAWN760
 
1.1%
CITY OF DES PLAINES671
 
1.0%
VILLAGE OF ARLINGTON HEIGHTS646
 
0.9%
CITY OF HARVEY590
 
0.9%
CITY OF EVANSTON579
 
0.8%
CITY OF BERWYN536
 
0.8%
VILLAGE OF NILES532
 
0.8%
VILLAGE OF SKOKIE531
 
0.8%
Other values (145)19055
27.5%
(Missing)3864
 
5.6%

MUNICIPALITY
Categorical

HIGH CARDINALITY
MISSING

Distinct130
Distinct (%)0.2%
Missing4828
Missing (%)7.0%
Memory size542.0 KiB
Chicago
40833 
Cicero
 
762
Oak Lawn
 
760
Des Plaines
 
671
Arlington Heights
 
646
Other values (125)
20859 

Unique

Unique2 ?
Unique (%)< 0.1%

Sample

1st rowChicago
2nd rowChicago
3rd rowChicago Heights
4th rowHodgkins
5th rowChicago

Common Values

ValueCountFrequency (%)
Chicago40833
58.9%
Cicero762
 
1.1%
Oak Lawn760
 
1.1%
Des Plaines671
 
1.0%
Arlington Heights646
 
0.9%
Harvey590
 
0.9%
Evanston579
 
0.8%
Berwyn536
 
0.8%
Niles532
 
0.8%
Skokie531
 
0.8%
Other values (120)18091
26.1%
(Missing)4828
 
7.0%

COMMENTS
Categorical

MISSING

Distinct2
Distinct (%)0.4%
Missing68840
Missing (%)99.3%
Memory size542.0 KiB
366 
need agency number
153 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowneed agency number
2nd row
3rd rowneed agency number
4th row
5th row

Common Values

ValueCountFrequency (%)
366
 
0.5%
need agency number153
 
0.2%
(Missing)68840
99.3%

Category Frequency Plot

2022-09-15T16:48:11.806897image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

SDELENGTH_SHAPE_
Real number (ℝ≥0)

MISSING

Distinct153
Distinct (%)0.2%
Missing4230
Missing (%)6.1%
Infinite0
Infinite (%)0.0%
Mean82683.16604
Minimum586.9864025
Maximum457699.1703
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.839185image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum586.9864025
5-th percentile37320.45551
Q175232.15856
median75232.15856
Q375232.15856
95-th percentile180348.8972
Maximum457699.1703
Range457112.1839
Interquartile range (IQR)0

Descriptive statistics

Standard deviation47674.10198
Coefficient of variation (CV)0.5765877659
Kurtosis26.08736938
Mean82683.16604
Median Absolute Deviation (MAD)0
Skewness4.112182946
Sum5385071921
Variance2272820000
MonotonicityNot monotonic
2022-09-15T16:48:11.878978image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
75232.1585641131
59.3%
58785.66743762
 
1.1%
93491.32965760
 
1.1%
180348.8972671
 
1.0%
209422.7815646
 
0.9%
100462.8833590
 
0.9%
77834.84925579
 
0.8%
45567.24944536
 
0.8%
137907.4907532
 
0.8%
92539.97273531
 
0.8%
Other values (143)18391
26.5%
(Missing)4230
 
6.1%
ValueCountFrequency (%)
586.986402548
 
0.1%
601.36149928
 
< 0.1%
723.690859254
 
0.1%
1031.39168271
0.1%
1042.094355170
0.2%
ValueCountFrequency (%)
457699.1703444
0.6%
243845.5803516
0.7%
227539.7961443
0.6%
209422.7815646
0.9%
191370.2046256
 
0.4%

GlobalID
Categorical

HIGH CARDINALITY
MISSING

Distinct156
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Memory size542.0 KiB
{B7D52FA7-596C-43F3-9CD7-8B92E6CEE1DE}
40833 
{3129FAE0-2C58-49CF-BA5E-6940B0E487BC}
 
762
{5081EB51-EB9A-4269-91AF-D74B921DC4B9}
 
760
{8587E105-3DE1-4637-8090-26D6E0D00C36}
 
671
{15F10119-D754-45D0-B85E-BC5FE0BB75BB}
 
646
Other values (151)
21823 

Unique

Unique5 ?
Unique (%)< 0.1%

Sample

1st row{B7D52FA7-596C-43F3-9CD7-8B92E6CEE1DE}
2nd row{B7D52FA7-596C-43F3-9CD7-8B92E6CEE1DE}
3rd row{56AA44F3-E9F9-40A4-A87E-D779FE11A31D}
4th row{6606665D-8363-4E94-A730-2E7FA8F81B0E}
5th row{B7D52FA7-596C-43F3-9CD7-8B92E6CEE1DE}

Common Values

ValueCountFrequency (%)
{B7D52FA7-596C-43F3-9CD7-8B92E6CEE1DE}40833
58.9%
{3129FAE0-2C58-49CF-BA5E-6940B0E487BC}762
 
1.1%
{5081EB51-EB9A-4269-91AF-D74B921DC4B9}760
 
1.1%
{8587E105-3DE1-4637-8090-26D6E0D00C36}671
 
1.0%
{15F10119-D754-45D0-B85E-BC5FE0BB75BB}646
 
0.9%
{E4277CED-6828-467E-BF1D-8C35CD593D0E}590
 
0.9%
{8E69B487-3437-483D-80C0-3A5623FAA496}579
 
0.8%
{AFF4609C-6112-4891-9C4B-93C160514E15}536
 
0.8%
{17CE7FD9-93F8-4190-ACD6-25AF4AE084A9}532
 
0.8%
{31DAEA72-231C-4E0E-8E12-775C40ACA2AF}531
 
0.8%
Other values (146)19055
27.5%
(Missing)3864
 
5.6%

created_user
Categorical

MISSING

Distinct5
Distinct (%)0.2%
Missing67027
Missing (%)96.6%
Memory size542.0 KiB
MHAMMER
786 
DARFA
590 
GIS
532 
SDE
345 
ENTGIS
79 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGIS
2nd rowGIS
3rd rowGIS
4th rowSDE
5th rowGIS

Common Values

ValueCountFrequency (%)
MHAMMER786
 
1.1%
DARFA590
 
0.9%
GIS532
 
0.8%
SDE345
 
0.5%
ENTGIS79
 
0.1%
(Missing)67027
96.6%

Category Frequency Plot

2022-09-15T16:48:11.917136image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

created_date
Real number (ℝ≥0)

MISSING

Distinct19
Distinct (%)0.8%
Missing67027
Missing (%)96.6%
Infinite0
Infinite (%)0.0%
Mean1.587978202 × 1012
Minimum1.504020964 × 1012
Maximum1.658327334 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:11.948062image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.504020964 × 1012
5-th percentile1.527782863 × 1012
Q11.531146556 × 1012
median1.611697853 × 1012
Q31.636138045 × 1012
95-th percentile1.643994945 × 1012
Maximum1.658327334 × 1012
Range1.5430637 × 1011
Interquartile range (IQR)1.04991489 × 1011

Descriptive statistics

Standard deviation4.618452902 × 1010
Coefficient of variation (CV)0.02908385579
Kurtosis-1.53174098
Mean1.587978202 × 1012
Median Absolute Deviation (MAD)2.4440192 × 1010
Skewness-0.2937227382
Sum3.703165167 × 1015
Variance2.133010721 × 1021
MonotonicityNot monotonic
2022-09-15T16:48:11.982652image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
1.636138045 × 1012444
 
0.6%
1.61532356 × 1012366
 
0.5%
1.611697853 × 1012361
 
0.5%
1.550053137 × 1012345
 
0.5%
1.528378313 × 1012200
 
0.3%
1.527782863 × 1012142
 
0.2%
1.531146305 × 1012117
 
0.2%
1.531146556 × 101273
 
0.1%
1.652906812 × 101254
 
0.1%
1.613598654 × 101247
 
0.1%
Other values (9)183
 
0.3%
(Missing)67027
96.6%
ValueCountFrequency (%)
1.504020964 × 101237
 
0.1%
1.508251649 × 101229
 
< 0.1%
1.516957241 × 101212
 
< 0.1%
1.527782863 × 1012142
0.2%
1.528378313 × 1012200
0.3%
ValueCountFrequency (%)
1.658327334 × 101228
< 0.1%
1.653597624 × 101226
< 0.1%
1.652906812 × 101254
0.1%
1.643994945 × 101224
< 0.1%
1.636408392 × 101214
 
< 0.1%

last_edited_user
Categorical

MISSING

Distinct6
Distinct (%)< 0.1%
Missing3864
Missing (%)5.6%
Memory size542.0 KiB
ENTGIS
50091 
DARFA
5588 
GIS
 
4719
WINGENTE
 
2218
MHAMMER
 
2113

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowENTGIS
2nd rowENTGIS
3rd rowDARFA
4th rowGIS
5th rowENTGIS

Common Values

ValueCountFrequency (%)
ENTGIS50091
72.2%
DARFA5588
 
8.1%
GIS4719
 
6.8%
WINGENTE2218
 
3.2%
MHAMMER2113
 
3.0%
SDE766
 
1.1%
(Missing)3864
 
5.6%

Category Frequency Plot

2022-09-15T16:48:12.021619image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

last_edited_date
Real number (ℝ≥0)

MISSING

Distinct93
Distinct (%)0.1%
Missing3864
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean1.573989554 × 1012
Minimum1.468571782 × 1012
Maximum1.658327334 × 1012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.057691image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.468571782 × 1012
5-th percentile1.468571782 × 1012
Q11.578322186 × 1012
median1.578322186 × 1012
Q31.578322186 × 1012
95-th percentile1.65089446 × 1012
Maximum1.658327334 × 1012
Range1.89755552 × 1011
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.181270173 × 1010
Coefficient of variation (CV)0.02656478985
Kurtosis1.681708606
Mean1.573989554 × 1012
Median Absolute Deviation (MAD)0
Skewness-0.8732581909
Sum1.030884458 × 1017
Variance1.748302026 × 1021
MonotonicityNot monotonic
2022-09-15T16:48:12.100400image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.578322186 × 101240833
58.9%
1.468571782 × 10123910
 
5.6%
1.65089446 × 10122218
 
3.2%
1.468571883 × 10121837
 
2.6%
1.61403032 × 10121308
 
1.9%
1.520437392 × 1012766
 
1.1%
1.654115953 × 1012671
 
1.0%
1.53858192 × 1012590
 
0.9%
1.582541978 × 1012536
 
0.8%
1.616522871 × 1012516
 
0.7%
Other values (83)12310
 
17.7%
(Missing)3864
 
5.6%
ValueCountFrequency (%)
1.468571782 × 10123910
5.6%
1.468571883 × 10121837
2.6%
1.482495746 × 101218
 
< 0.1%
1.520437392 × 1012766
 
1.1%
1.527852069 × 101289
 
0.1%
ValueCountFrequency (%)
1.658327334 × 1012293
0.4%
1.654290361 × 1012164
 
0.2%
1.654276286 × 101224
 
< 0.1%
1.654115953 × 1012671
1.0%
1.654111167 × 101244
 
0.1%

muniCnclMmbr
Categorical

MISSING

Distinct7
Distinct (%)< 0.1%
Missing50793
Missing (%)73.2%
Memory size542.0 KiB
SCM
4299 
NWMC
3402 
SWCM
2975 
NCCM
2552 
CCM
2415 
Other values (2)
2923 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowCCM
2nd rowSCM
3rd rowNSCM
4th rowSWCM
5th rowCCM

Common Values

ValueCountFrequency (%)
SCM4299
 
6.2%
NWMC3402
 
4.9%
SWCM2975
 
4.3%
NCCM2552
 
3.7%
CCM2415
 
3.5%
NSCM2383
 
3.4%
SCM&SWCM540
 
0.8%
(Missing)50793
73.2%

Category Frequency Plot

2022-09-15T16:48:12.145210image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

cbasOptIn
Categorical

MISSING

Distinct2
Distinct (%)< 0.1%
Missing6455
Missing (%)9.3%
Memory size542.0 KiB
NO
47327 
YES
15577 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNO
2nd rowNO
3rd rowNO
4th rowNO
5th rowNO

Common Values

ValueCountFrequency (%)
NO47327
68.2%
YES15577
 
22.5%
(Missing)6455
 
9.3%

Category Frequency Plot

2022-09-15T16:48:12.179322image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

SHAPE.STArea()
Real number (ℝ≥0)

MISSING

Distinct156
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean4053654558
Minimum128821.0204
Maximum6383804206
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.212660image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum128821.0204
5-th percentile67288784.68
Q1215655541.6
median6383804206
Q36383804206
95-th percentile6383804206
Maximum6383804206
Range6383675385
Interquartile range (IQR)6168148664

Descriptive statistics

Standard deviation2999567204
Coefficient of variation (CV)0.7399661616
Kurtosis-1.73446414
Mean4053654558
Median Absolute Deviation (MAD)0
Skewness-0.5121132777
Sum2.654941053 × 1014
Variance8.99740341 × 1018
MonotonicityNot monotonic
2022-09-15T16:48:12.254067image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
638380420640833
58.9%
163603357.3762
 
1.1%
238977618.5760
 
1.1%
403656291.8671
 
1.0%
469666697.3646
 
0.9%
170802825.2590
 
0.9%
217977852.3579
 
0.8%
108746057.8536
 
0.8%
164791090.5532
 
0.8%
280431126.6531
 
0.8%
Other values (146)19055
27.5%
(Missing)3864
 
5.6%
ValueCountFrequency (%)
128821.02041
 
< 0.1%
1328993.471
 
< 0.1%
2215601.9621
 
< 0.1%
3689020.9592
 
< 0.1%
9389449.63543
0.1%
ValueCountFrequency (%)
638380420640833
58.9%
600242227.5444
 
0.6%
591243235308
 
0.4%
540637860.2516
 
0.7%
520575976.253
 
0.1%

SHAPE.STLength()
Real number (ℝ≥0)

MISSING

Distinct156
Distinct (%)0.2%
Missing3864
Missing (%)5.6%
Infinite0
Infinite (%)0.0%
Mean584798.8596
Minimum7834.099365
Maximum868367.1075
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.295126image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum7834.099365
5-th percentile45632.54929
Q1123820.743
median868367.1075
Q3868367.1075
95-th percentile868367.1075
Maximum868367.1075
Range860533.0081
Interquartile range (IQR)744546.3645

Descriptive statistics

Standard deviation368390.1653
Coefficient of variation (CV)0.6299433715
Kurtosis-1.635105078
Mean584798.8596
Median Absolute Deviation (MAD)0
Skewness-0.5600997819
Sum3.830140131 × 1010
Variance1.357113139 × 1011
MonotonicityNot monotonic
2022-09-15T16:48:12.336902image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
868367.107540833
58.9%
58785.66743762
 
1.1%
93652.73598760
 
1.1%
187036.2705671
 
1.0%
210482.1707646
 
0.9%
94612.67535590
 
0.9%
82077.48048579
 
0.8%
45567.24944536
 
0.8%
137953.9349532
 
0.8%
94226.42532531
 
0.8%
Other values (146)19055
27.5%
(Missing)3864
 
5.6%
ValueCountFrequency (%)
7834.0993651
 
< 0.1%
8080.5304431
 
< 0.1%
13744.59112
 
< 0.1%
15777.688551
 
< 0.1%
16030.6585657
0.1%
ValueCountFrequency (%)
868367.107540833
58.9%
540761.282422
 
< 0.1%
469305.116324
 
< 0.1%
425183.7255444
 
0.6%
398887.235126
 
< 0.1%

pri_neigh
Categorical

HIGH CARDINALITY
MISSING

Distinct98
Distinct (%)0.2%
Missing28527
Missing (%)41.1%
Memory size542.0 KiB
Austin
 
2427
Englewood
 
1855
Garfield Park
 
1815
Humboldt Park
 
1469
South Shore
 
1416
Other values (93)
31850 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO'Hare
2nd rowStreeterville
3rd rowAuburn Gresham
4th rowWest Pullman
5th rowLower West Side

Common Values

ValueCountFrequency (%)
Austin2427
 
3.5%
Englewood1855
 
2.7%
Garfield Park1815
 
2.6%
Humboldt Park1469
 
2.1%
South Shore1416
 
2.0%
North Lawndale1171
 
1.7%
Roseland1130
 
1.6%
Auburn Gresham1040
 
1.5%
Uptown1025
 
1.5%
Little Village973
 
1.4%
Other values (88)26511
38.2%
(Missing)28527
41.1%

sec_neigh
Categorical

HIGH CARDINALITY
MISSING

Distinct78
Distinct (%)0.2%
Missing28527
Missing (%)41.1%
Memory size542.0 KiB
AUSTIN
 
2427
SOUTH SHORE, GRAND CROSSING
 
2301
ENGLEWOOD
 
1855
GARFIELD PARK
 
1815
WASHINGTON HEIGHTS,ROSELAND
 
1621
Other values (73)
30813 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowOHARE
2nd rowSTREETERVILLE
3rd rowAUBURN GRESHAM
4th rowWEST PULLMAN
5th rowLOWER WEST SIDE

Common Values

ValueCountFrequency (%)
AUSTIN2427
 
3.5%
SOUTH SHORE, GRAND CROSSING2301
 
3.3%
ENGLEWOOD1855
 
2.7%
GARFIELD PARK1815
 
2.6%
WASHINGTON HEIGHTS,ROSELAND1621
 
2.3%
HUMBOLDT PARK1469
 
2.1%
MARQUETTE PARK,GAGE PARK1208
 
1.7%
NORTH LAWNDALE1171
 
1.7%
AUBURN GRESHAM1040
 
1.5%
UPTOWN1025
 
1.5%
Other values (68)24900
35.9%
(Missing)28527
41.1%

shape_area
Real number (ℝ≥0)

MISSING

Distinct98
Distinct (%)0.2%
Missing28527
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean92808854.55
Minimum882405.0862
Maximum371835607.7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.377466image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum882405.0862
5-th percentile28800760.14
Q158507728.42
median89487422.02
Q3121959105.5
95-th percentile173600015
Maximum371835607.7
Range370953202.6
Interquartile range (IQR)63451377.05

Descriptive statistics

Standard deviation50429794.56
Coefficient of variation (CV)0.5433726642
Kurtosis6.19065661
Mean92808854.55
Median Absolute Deviation (MAD)31195902.75
Skewness1.613433857
Sum3.789571149 × 1012
Variance2.54316418 × 1015
MonotonicityNot monotonic
2022-09-15T16:48:12.417968image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
170037750.82427
 
3.5%
1736000151855
 
2.7%
89976069.591815
 
2.6%
125010425.61469
 
2.1%
81812716.391416
 
2.0%
89487422.021171
 
1.7%
134313706.71130
 
1.6%
105065353.61040
 
1.5%
65095642.841025
 
1.5%
127998297.8973
 
1.4%
Other values (88)26511
38.2%
(Missing)28527
41.1%
ValueCountFrequency (%)
882405.08629
< 0.1%
1650645.84211
< 0.1%
2162137.97120
< 0.1%
2775228.3799
< 0.1%
3365778.97122
< 0.1%
ValueCountFrequency (%)
371835607.7265
 
0.4%
303797059.7256
 
0.4%
1736000151855
2.7%
170037750.82427
3.5%
145965741.4112
 
0.2%

shape_len
Real number (ℝ≥0)

MISSING

Distinct98
Distinct (%)0.2%
Missing28527
Missing (%)41.1%
Infinite0
Infinite (%)0.0%
Mean45232.7565
Minimum6099.310646
Maximum173625.9847
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.458189image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum6099.310646
5-th percentile24359.18962
Q136568.46429
median44959.45966
Q352640.90756
95-th percentile61856.51647
Maximum173625.9847
Range167526.674
Interquartile range (IQR)16072.44327

Descriptive statistics

Standard deviation15846.73815
Coefficient of variation (CV)0.3503376617
Kurtosis26.27783087
Mean45232.7565
Median Absolute Deviation (MAD)8334.856578
Skewness3.353031947
Sum1846943914
Variance251119109.9
MonotonicityNot monotonic
2022-09-15T16:48:12.498141image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55473.345912427
 
3.5%
56144.046051855
 
2.7%
44460.919221815
 
2.6%
46126.751351469
 
2.1%
44249.645181416
 
2.0%
44959.459661171
 
1.7%
56632.795431130
 
1.6%
46757.721721040
 
1.5%
46972.790181025
 
1.5%
49904.04003973
 
1.4%
Other values (88)26511
38.2%
(Missing)28527
41.1%
ValueCountFrequency (%)
6099.31064611
 
< 0.1%
6864.24715620
 
< 0.1%
7567.385589
 
< 0.1%
8503.033133154
0.2%
9154.5671159
 
< 0.1%
ValueCountFrequency (%)
173625.9847265
0.4%
80389.8718256
0.4%
80368.37438429
0.6%
74493.8216123
 
0.2%
73692.38213112
 
0.2%

OBJECTID_right
Real number (ℝ≥0)

MISSING

Distinct88
Distinct (%)37.0%
Missing69121
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1351.995798
Minimum64
Maximum1987
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.539118image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum64
5-th percentile489
Q11067.5
median1284
Q31781
95-th percentile1867.45
Maximum1987
Range1923
Interquartile range (IQR)713.5

Descriptive statistics

Standard deviation453.0512541
Coefficient of variation (CV)0.3350981228
Kurtosis-0.9920334808
Mean1351.995798
Median Absolute Deviation (MAD)497
Skewness-0.4046713342
Sum321775
Variance205255.4388
MonotonicityNot monotonic
2022-09-15T16:48:12.581735image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
178169
 
0.1%
110924
 
< 0.1%
80012
 
< 0.1%
124710
 
< 0.1%
4898
 
< 0.1%
12845
 
< 0.1%
18505
 
< 0.1%
8853
 
< 0.1%
18003
 
< 0.1%
11423
 
< 0.1%
Other values (78)96
 
0.1%
(Missing)69121
99.7%
ValueCountFrequency (%)
641
< 0.1%
2741
< 0.1%
3421
< 0.1%
4441
< 0.1%
4691
< 0.1%
ValueCountFrequency (%)
19871
< 0.1%
19491
< 0.1%
19471
< 0.1%
19391
< 0.1%
19301
< 0.1%

CFNAME
Categorical

HIGH CARDINALITY
MISSING

Distinct86
Distinct (%)36.1%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
Lincoln (Abraham) Park
69 
Humboldt Park
24 
Douglas Park
12 
Washington Park
 
10
Lincolnwood Centennial Park
 
8
Other values (81)
115 

Unique

Unique60 ?
Unique (%)25.2%

Sample

1st rowNorth Shore Sculpture Park
2nd rowLincoln (Abraham) Park
3rd rowMoore Park
4th rowWashington Park
5th rowSherman Park

Common Values

ValueCountFrequency (%)
Lincoln (Abraham) Park69
 
0.1%
Humboldt Park24
 
< 0.1%
Douglas Park12
 
< 0.1%
Washington Park10
 
< 0.1%
Lincolnwood Centennial Park8
 
< 0.1%
Northerly Island Park5
 
< 0.1%
Loyola Park5
 
< 0.1%
Wood Park3
 
< 0.1%
Millennium Park3
 
< 0.1%
Rainbow Beach Park3
 
< 0.1%
Other values (76)96
 
0.1%
(Missing)69121
99.7%

CFTYPE
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
Park
238 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPark
2nd rowPark
3rd rowPark
4th rowPark
5th rowPark

Common Values

ValueCountFrequency (%)
Park238
 
0.3%
(Missing)69121
99.7%

Category Frequency Plot

2022-09-15T16:48:12.617164image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

CFSUBTYPE
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)0.4%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
Park
238 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPark
2nd rowPark
3rd rowPark
4th rowPark
5th rowPark

Common Values

ValueCountFrequency (%)
Park238
 
0.3%
(Missing)69121
99.7%

Category Frequency Plot

2022-09-15T16:48:12.642069image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

ADDRESS
Categorical

HIGH CARDINALITY
MISSING

Distinct74
Distinct (%)31.1%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
200 W Fullerton Pkwy
69 
Unknown
24 
1400 N Humboldt Dr
24 
1613 S Sacramento Dr
12 
5531 S Dr Martin Luther King Jr Dr
10 
Other values (69)
99 

Unique

Unique51 ?
Unique (%)21.4%

Sample

1st rowUnknown
2nd row200 W Fullerton Pkwy
3rd row5085 W Adams St
4th row5531 S Dr Martin Luther King Jr Dr
5th row1301 W 52nd St

Common Values

ValueCountFrequency (%)
200 W Fullerton Pkwy69
 
0.1%
Unknown24
 
< 0.1%
1400 N Humboldt Dr24
 
< 0.1%
1613 S Sacramento Dr12
 
< 0.1%
5531 S Dr Martin Luther King Jr Dr10
 
< 0.1%
1400 S Lynn White Dr5
 
< 0.1%
1230 W Greenleaf Ave5
 
< 0.1%
205 E Randolph St3
 
< 0.1%
2915 N Leavitt St3
 
< 0.1%
6700 S Kedzie Ave3
 
< 0.1%
Other values (64)80
 
0.1%
(Missing)69121
99.7%

GNISCODE
Real number (ℝ≥0)

MISSING

Distinct70
Distinct (%)33.8%
Missing69152
Missing (%)99.7%
Infinite0
Infinite (%)0.0%
Mean1073942.845
Minimum403466
Maximum2042449
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:12.674371image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum403466
5-th percentile407341
Q1410679
median423601
Q31829853
95-th percentile1835546.3
Maximum2042449
Range1638983
Interquartile range (IQR)1419174

Descriptive statistics

Standard deviation712778.3424
Coefficient of variation (CV)0.6637023054
Kurtosis-1.980790899
Mean1073942.845
Median Absolute Deviation (MAD)17437
Skewness0.1555318587
Sum222306169
Variance5.080529654 × 1011
MonotonicityNot monotonic
2022-09-15T16:48:12.715951image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
182985369
 
0.1%
41067924
 
< 0.1%
40734112
 
< 0.1%
42056710
 
< 0.1%
4236015
 
< 0.1%
4127325
 
< 0.1%
4086733
 
< 0.1%
20424493
 
< 0.1%
4034663
 
< 0.1%
4130283
 
< 0.1%
Other values (60)70
 
0.1%
(Missing)69152
99.7%
ValueCountFrequency (%)
4034663
< 0.1%
4037201
 
< 0.1%
4037291
 
< 0.1%
4041821
 
< 0.1%
4053761
 
< 0.1%
ValueCountFrequency (%)
20424493
< 0.1%
20356591
 
< 0.1%
20267891
 
< 0.1%
20267761
 
< 0.1%
18668821
 
< 0.1%

COMMENT
Categorical

MISSING

Distinct3
Distinct (%)42.9%
Missing69352
Missing (%)> 99.9%
Memory size542.0 KiB
Additional GNIS code of 1831526.
Google states Harrington Park
Nature Center is inside of Park boundary.

Unique

Unique2 ?
Unique (%)28.6%

Sample

1st rowGoogle states Harrington Park
2nd rowAdditional GNIS code of 1831526.
3rd rowAdditional GNIS code of 1831526.
4th rowAdditional GNIS code of 1831526.
5th rowAdditional GNIS code of 1831526.

Common Values

ValueCountFrequency (%)
Additional GNIS code of 1831526.5
 
< 0.1%
Google states Harrington Park1
 
< 0.1%
Nature Center is inside of Park boundary.1
 
< 0.1%
(Missing)69352
> 99.9%

Category Frequency Plot

2022-09-15T16:48:13.055282image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

SOURCE
Categorical

MISSING

Distinct8
Distinct (%)3.4%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
CGI
117 
CGIL
77 
GI
22 
CG
 
11
GIL
 
8
Other values (3)
 
3

Unique

Unique3 ?
Unique (%)1.3%

Sample

1st rowCGI
2nd rowCGI
3rd rowCGIL
4th rowCGIL
5th rowCGIL

Common Values

ValueCountFrequency (%)
CGI117
 
0.2%
CGIL77
 
0.1%
GI22
 
< 0.1%
CG11
 
< 0.1%
GIL8
 
< 0.1%
CI1
 
< 0.1%
G1
 
< 0.1%
CGL1
 
< 0.1%
(Missing)69121
99.7%

Category Frequency Plot

2022-09-15T16:48:13.091554image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Jurisdiction
Categorical

MISSING

Distinct34
Distinct (%)15.6%
Missing69141
Missing (%)99.7%
Memory size542.0 KiB
CHICAGO PARK DISTRICT
148 
METRO WATER RECLM DIST
 
13
IL DEPT-MILITARY AFFRS
 
10
CHICAGO HOUSING AUTH
 
4
BURBANK PARK DIST
 
3
Other values (29)
40 

Unique

Unique22 ?
Unique (%)10.1%

Sample

1st rowMETRO WATER RECLM DIST
2nd rowCHICAGO PARK DISTRICT
3rd rowCHICAGO PARK DISTRICT
4th rowIL DEPT-MILITARY AFFRS
5th rowCHICAGO PARK DISTRICT

Common Values

ValueCountFrequency (%)
CHICAGO PARK DISTRICT148
 
0.2%
METRO WATER RECLM DIST13
 
< 0.1%
IL DEPT-MILITARY AFFRS10
 
< 0.1%
CHICAGO HOUSING AUTH4
 
< 0.1%
BURBANK PARK DIST3
 
< 0.1%
STATE OF ILLINOIS3
 
< 0.1%
CITY OF CHICAGO3
 
< 0.1%
CHICAGO PARK DISTRICT 3
 
< 0.1%
NORTHLAKE CITY OF3
 
< 0.1%
OLYMPIA FIELDS PK DIST2
 
< 0.1%
Other values (24)26
 
< 0.1%
(Missing)69141
99.7%

Community
Categorical

MISSING

Distinct26
Distinct (%)10.9%
Missing69121
Missing (%)99.7%
Memory size542.0 KiB
Chicago
194 
Lincolnwood
 
8
Northlake
 
4
Evanston
 
3
Glenview
 
2
Other values (21)
27 

Unique

Unique15 ?
Unique (%)6.3%

Sample

1st rowSkokie
2nd rowChicago
3rd rowChicago
4th rowChicago
5th rowChicago

Common Values

ValueCountFrequency (%)
Chicago194
 
0.3%
Lincolnwood8
 
< 0.1%
Northlake4
 
< 0.1%
Evanston3
 
< 0.1%
Glenview2
 
< 0.1%
Schaumburg2
 
< 0.1%
Skokie2
 
< 0.1%
Wilmette2
 
< 0.1%
Cicero2
 
< 0.1%
Olympia Fields2
 
< 0.1%
Other values (16)17
 
< 0.1%
(Missing)69121
99.7%

STATEFP_left
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean17
Minimum17
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.119946image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile17
Q117
median17
Q317
95-th percentile17
Maximum17
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean17
Median Absolute Deviation (MAD)0
Skewness0
Sum1140564
Variance0
MonotonicityIncreasing
2022-09-15T16:48:13.146596image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1767092
96.7%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
1767092
96.7%
ValueCountFrequency (%)
1767092
96.7%

COUNTYFP_left
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean32.94094676
Minimum31
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.173614image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile31
Q131
median31
Q331
95-th percentile31
Maximum197
Range166
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.02963099
Coefficient of variation (CV)0.4866171912
Kurtosis90.7153568
Mean32.94094676
Median Absolute Deviation (MAD)0
Skewness9.404798634
Sum2210074
Variance256.9490696
MonotonicityNot monotonic
2022-09-15T16:48:13.202294image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3165441
94.4%
43630
 
0.9%
197563
 
0.8%
97269
 
0.4%
89124
 
0.2%
11131
 
< 0.1%
9323
 
< 0.1%
6311
 
< 0.1%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
3165441
94.4%
43630
 
0.9%
6311
 
< 0.1%
89124
 
0.2%
9323
 
< 0.1%
ValueCountFrequency (%)
197563
0.8%
11131
 
< 0.1%
97269
0.4%
9323
 
< 0.1%
89124
 
0.2%

COUSUBFP
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean27810.72305
Minimum250
Maximum83947
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.240205image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum250
5-th percentile7939
Q114000
median14000
Q345447
95-th percentile76212
Maximum83947
Range83697
Interquartile range (IQR)31447

Descriptive statistics

Standard deviation23052.24188
Coefficient of variation (CV)0.8288976103
Kurtosis-0.08947437485
Mean27810.72305
Median Absolute Deviation (MAD)0
Skewness1.200238144
Sum1865877031
Variance531405855.6
MonotonicityNot monotonic
2022-09-15T16:48:13.281076image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1400040782
58.8%
751982179
 
3.1%
835311914
 
2.8%
621331801
 
2.6%
461621463
 
2.1%
79391400
 
2.0%
454471241
 
1.8%
811001171
 
1.7%
530131096
 
1.6%
431201055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
250187
0.3%
69831
 
< 0.1%
302529
 
< 0.1%
309011
 
< 0.1%
383195
0.1%
ValueCountFrequency (%)
8394747
 
0.1%
835311914
2.8%
8241311
 
< 0.1%
811001171
1.7%
8103515
 
< 0.1%

COUSUBNS
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean447173.926
Minimum422238
Maximum2394709
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.321226image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum422238
5-th percentile428682
Q1428803
median428803
Q3429252
95-th percentile429927
Maximum2394709
Range1972471
Interquartile range (IQR)449

Descriptive statistics

Standard deviation187234.7883
Coefficient of variation (CV)0.4187068553
Kurtosis101.2878905
Mean447173.926
Median Absolute Deviation (MAD)0
Skewness10.14028328
Sum3.000179305 × 1010
Variance3.505686596 × 1010
MonotonicityNot monotonic
2022-09-15T16:48:13.362856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42880340782
58.8%
4222382179
 
3.1%
4299581914
 
2.8%
4296081801
 
2.6%
4293101463
 
2.1%
4287061400
 
2.0%
4292981241
 
1.8%
4299271171
 
1.7%
4294471096
 
1.6%
4292521055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
4222382179
3.1%
428571187
 
0.3%
42857831
 
< 0.1%
42862129
 
< 0.1%
42862311
 
< 0.1%
ValueCountFrequency (%)
2394709580
 
0.8%
184816166
 
0.1%
42997047
 
0.1%
4299581914
2.8%
42994511
 
< 0.1%

AFFGEOID
Categorical

HIGH CARDINALITY
MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Memory size542.0 KiB
0600000US1703114000
40782 
0600000US1703175198
 
2179
0600000US1703183531
 
1914
0600000US1703162133
 
1801
0600000US1703146162
 
1463
Other values (66)
18953 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0600000US1703114000
2nd row0600000US1719738583
3rd row0600000US1703114000
4th row0600000US1703106561
5th row0600000US1703145447

Common Values

ValueCountFrequency (%)
0600000US170311400040782
58.8%
0600000US17031751982179
 
3.1%
0600000US17031835311914
 
2.8%
0600000US17031621331801
 
2.6%
0600000US17031461621463
 
2.1%
0600000US17031079391400
 
2.0%
0600000US17031454471241
 
1.8%
0600000US17031811001171
 
1.7%
0600000US17031530131096
 
1.6%
0600000US17031431201055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%

GEOID_left
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean1703321905
Minimum1703103831
Maximum1719781035
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.404346image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1703103831
5-th percentile1703110474
Q11703114000
median1703114000
Q31703146162
95-th percentile1703183531
Maximum1719781035
Range16677204
Interquartile range (IQR)32162

Descriptive statistics

Standard deviation1604427.292
Coefficient of variation (CV)0.0009419401507
Kurtosis90.61408243
Mean1703321905
Median Absolute Deviation (MAD)0
Skewness9.398616348
Sum1.142792733 × 1014
Variance2.574186936 × 1012
MonotonicityNot monotonic
2022-09-15T16:48:13.446571image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
170311400040782
58.8%
17031751982179
 
3.1%
17031835311914
 
2.8%
17031621331801
 
2.6%
17031461621463
 
2.1%
17031079391400
 
2.0%
17031454471241
 
1.8%
17031811001171
 
1.7%
17031530131096
 
1.6%
17031431201055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
170310383195
 
0.1%
1703105586536
 
0.8%
17031065611025
1.5%
17031079391400
2.0%
1703110474332
 
0.5%
ValueCountFrequency (%)
171978103515
 
< 0.1%
171977621217
 
< 0.1%
171976030020
 
< 0.1%
171975259726
 
< 0.1%
1719749958113
0.2%

NAME_left
Categorical

HIGH CARDINALITY
MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Memory size542.0 KiB
Chicago
40782 
Thornton
 
2179
Worth
 
1914
Proviso
 
1801
Maine
 
1463
Other values (66)
18953 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowChicago
2nd rowJoliet
3rd rowChicago
4th rowBloom
5th rowLyons

Common Values

ValueCountFrequency (%)
Chicago40782
58.8%
Thornton2179
 
3.1%
Worth1914
 
2.8%
Proviso1801
 
2.6%
Maine1463
 
2.1%
Bremen1400
 
2.0%
Lyons1241
 
1.8%
Wheeling1171
 
1.7%
Niles1096
 
1.6%
Leyden1055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%

LSAD
Real number (ℝ≥0)

MISSING

Distinct2
Distinct (%)< 0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean32.28656174
Minimum25
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.478743image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile25
Q125
median25
Q344
95-th percentile44
Maximum44
Range19
Interquartile range (IQR)19

Descriptive statistics

Standard deviation9.238612624
Coefficient of variation (CV)0.2861442076
Kurtosis-1.770434108
Mean32.28656174
Median Absolute Deviation (MAD)0
Skewness0.4791854228
Sum2166170
Variance85.35196322
MonotonicityNot monotonic
2022-09-15T16:48:13.507167image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
2541362
59.6%
4425730
37.1%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
2541362
59.6%
4425730
37.1%
ValueCountFrequency (%)
4425730
37.1%
2541362
59.6%

ALAND_left
Real number (ℝ≥0)

MISSING

Distinct71
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean384536566.9
Minimum6422499
Maximum582989656
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.544541image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum6422499
5-th percentile32323978
Q192388145
median582989656
Q3582989656
95-th percentile582989656
Maximum582989656
Range576567157
Interquartile range (IQR)490601511

Descriptive statistics

Standard deviation247830741.3
Coefficient of variation (CV)0.6444920006
Kurtosis-1.760139372
Mean384536566.9
Median Absolute Deviation (MAD)0
Skewness-0.4609514782
Sum2.579932734 × 1013
Variance6.142007634 × 1016
MonotonicityNot monotonic
2022-09-15T16:48:13.586205image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58298965640782
58.8%
1214635512179
 
3.1%
823975041914
 
2.8%
769727541801
 
2.6%
671140191463
 
2.1%
977566891400
 
2.0%
941606081241
 
1.8%
929974141171
 
1.7%
550580181096
 
1.6%
516040801055
 
1.5%
Other values (61)12990
 
18.7%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
642249954
 
0.1%
9499981343
0.5%
10112484536
0.8%
10427485149
 
0.2%
11423514332
0.5%
ValueCountFrequency (%)
58298965640782
58.8%
12846871492
 
0.1%
1214635512179
 
3.1%
12030851331
 
< 0.1%
1201775321025
 
1.5%

AWATER_left
Real number (ℝ≥0)

MISSING
ZEROS

Distinct63
Distinct (%)0.1%
Missing2267
Missing (%)3.3%
Infinite0
Infinite (%)0.0%
Mean10986931.83
Minimum0
Maximum17565657
Zeros4264
Zeros (%)6.1%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.626984image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1875699
median17565657
Q317565657
95-th percentile17565657
Maximum17565657
Range17565657
Interquartile range (IQR)16689958

Descriptive statistics

Standard deviation8209997.098
Coefficient of variation (CV)0.7472511186
Kurtosis-1.777676082
Mean10986931.83
Median Absolute Deviation (MAD)0
Skewness-0.4550970197
Sum7.371352301 × 1011
Variance6.740405234 × 1013
MonotonicityNot monotonic
2022-09-15T16:48:13.669409image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1756565740782
58.8%
04264
 
6.1%
12552642179
 
3.1%
8756991914
 
2.8%
5621801
 
2.6%
6405451463
 
2.1%
2951431400
 
2.0%
14616221241
 
1.8%
3177431171
 
1.7%
6287931025
 
1.5%
Other values (53)9852
 
14.2%
(Missing)2267
 
3.3%
ValueCountFrequency (%)
04264
6.1%
5621801
2.6%
479454
 
0.1%
155497
 
< 0.1%
43529149
 
0.2%
ValueCountFrequency (%)
1756565740782
58.8%
58402415
 
< 0.1%
529784020
 
< 0.1%
4274345768
 
1.1%
413151831
 
< 0.1%

STATEFP_right
Real number (ℝ≥0)

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean17
Minimum17
Maximum17
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.702041image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile17
Q117
median17
Q317
95-th percentile17
Maximum17
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean17
Median Absolute Deviation (MAD)0
Skewness0
Sum1141414
Variance0
MonotonicityIncreasing
2022-09-15T16:48:13.729274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
1767142
96.8%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
1767142
96.8%
ValueCountFrequency (%)
1767142
96.8%

COUNTYFP_right
Real number (ℝ≥0)

MISSING

Distinct8
Distinct (%)< 0.1%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean32.93899497
Minimum31
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.756662image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile31
Q131
median31
Q331
95-th percentile31
Maximum197
Range166
Interquartile range (IQR)0

Descriptive statistics

Standard deviation16.01504991
Coefficient of variation (CV)0.4862033565
Kurtosis90.83524721
Mean32.93899497
Median Absolute Deviation (MAD)0
Skewness9.409745905
Sum2211590
Variance256.4818237
MonotonicityNot monotonic
2022-09-15T16:48:13.785815image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3165490
94.4%
43630
 
0.9%
197562
 
0.8%
97271
 
0.4%
89124
 
0.2%
11131
 
< 0.1%
9323
 
< 0.1%
6311
 
< 0.1%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
3165490
94.4%
43630
 
0.9%
6311
 
< 0.1%
89124
 
0.2%
9323
 
< 0.1%
ValueCountFrequency (%)
197562
0.8%
11131
 
< 0.1%
97271
0.4%
9323
 
< 0.1%
89124
 
0.2%

TRACTCE
Real number (ℝ≥0)

MISSING

Distinct1697
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean586542.5963
Minimum102
Maximum980100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.823324image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum102
5-th percentile40402
Q1292500
median750500
Q3822500
95-th percentile841207.95
Maximum980100
Range979998
Interquartile range (IQR)530000

Descriptive statistics

Standard deviation284917.857
Coefficient of variation (CV)0.485758168
Kurtosis-1.04415097
Mean586542.5963
Median Absolute Deviation (MAD)88300
Skewness-0.723856047
Sum3.9381643 × 1010
Variance8.117818524 × 1010
MonotonicityNot monotonic
2022-09-15T16:48:13.865692image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
431400310
 
0.4%
231500283
 
0.4%
839100258
 
0.4%
231200219
 
0.3%
808100208
 
0.3%
31200189
 
0.3%
10300182
 
0.3%
252202181
 
0.3%
252000179
 
0.3%
491000174
 
0.3%
Other values (1687)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
10210
 
< 0.1%
1031
 
< 0.1%
1010082
0.1%
1020161
0.1%
1020290
0.1%
ValueCountFrequency (%)
98010031
 
< 0.1%
980000124
0.2%
8907032
 
< 0.1%
8907027
 
< 0.1%
8907013
 
< 0.1%

GEOID_right
Real number (ℝ≥0)

MISSING

Distinct1710
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean1.703352554 × 1010
Minimum1.70310101 × 1010
Maximum1.71979801 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.906081image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.70310101 × 1010
5-th percentile1.70310404 × 1010
Q11.70312925 × 1010
median1.70317505 × 1010
Q31.70318225 × 1010
95-th percentile1.70318419 × 1010
Maximum1.71979801 × 1010
Range166970000
Interquartile range (IQR)530000

Descriptive statistics

Standard deviation16052437.2
Coefficient of variation (CV)0.0009424025088
Kurtosis90.65709602
Mean1.703352554 × 1010
Median Absolute Deviation (MAD)88300
Skewness9.398201256
Sum1.143664972 × 1015
Variance2.576807401 × 1014
MonotonicityNot monotonic
2022-09-15T16:48:13.948808image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1.70314314 × 1010310
 
0.4%
1.70312315 × 1010283
 
0.4%
1.70318391 × 1010258
 
0.4%
1.70312312 × 1010219
 
0.3%
1.70318081 × 1010208
 
0.3%
1.70310312 × 1010189
 
0.3%
1.70310103 × 1010182
 
0.3%
1.70312522 × 1010181
 
0.3%
1.7031252 × 1010179
 
0.3%
1.7031491 × 1010174
 
0.3%
Other values (1700)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
1.70310101 × 101082
0.1%
1.70310102 × 101061
 
0.1%
1.70310102 × 101090
0.1%
1.70310103 × 1010182
0.3%
1.70310104 × 101048
 
0.1%
ValueCountFrequency (%)
1.71979801 × 10109
 
< 0.1%
1.71978841 × 10103
 
< 0.1%
1.719788381 × 101033
< 0.1%
1.719788381 × 101013
 
< 0.1%
1.719788381 × 101016
< 0.1%

NAME_right
Real number (ℝ≥0)

MISSING

Distinct1697
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean5865.425963
Minimum1.02
Maximum9801
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:13.990527image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.02
5-th percentile404.02
Q12925
median7505
Q38225
95-th percentile8412.0795
Maximum9801
Range9799.98
Interquartile range (IQR)5300

Descriptive statistics

Standard deviation2849.17857
Coefficient of variation (CV)0.485758168
Kurtosis-1.04415097
Mean5865.425963
Median Absolute Deviation (MAD)883
Skewness-0.723856047
Sum393816430
Variance8117818.524
MonotonicityNot monotonic
2022-09-15T16:48:14.031848image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4314310
 
0.4%
2315283
 
0.4%
8391258
 
0.4%
2312219
 
0.3%
8081208
 
0.3%
312189
 
0.3%
103182
 
0.3%
2522.02181
 
0.3%
2520179
 
0.3%
4910174
 
0.3%
Other values (1687)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
1.0210
 
< 0.1%
1.031
 
< 0.1%
10182
0.1%
102.0161
0.1%
102.0290
0.1%
ValueCountFrequency (%)
980131
 
< 0.1%
9800124
0.2%
8907.032
 
< 0.1%
8907.027
 
< 0.1%
8907.013
 
< 0.1%

NAMELSAD
Categorical

HIGH CARDINALITY
MISSING

Distinct1697
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Memory size542.0 KiB
Census Tract 4314
 
310
Census Tract 2315
 
283
Census Tract 8391
 
258
Census Tract 2312
 
219
Census Tract 8081
 
208
Other values (1692)
65864 

Unique

Unique108 ?
Unique (%)0.2%

Sample

1st rowCensus Tract 9800
2nd rowCensus Tract 8823
3rd rowCensus Tract 814.03
4th rowCensus Tract 8290
5th rowCensus Tract 8202.02

Common Values

ValueCountFrequency (%)
Census Tract 4314310
 
0.4%
Census Tract 2315283
 
0.4%
Census Tract 8391258
 
0.4%
Census Tract 2312219
 
0.3%
Census Tract 8081208
 
0.3%
Census Tract 312189
 
0.3%
Census Tract 103182
 
0.3%
Census Tract 2522.02181
 
0.3%
Census Tract 2520179
 
0.3%
Census Tract 4910174
 
0.3%
Other values (1687)64959
93.7%
(Missing)2217
 
3.2%

MTFCC
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing2217
Missing (%)3.2%
Memory size542.0 KiB
G5020
67142 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowG5020
2nd rowG5020
3rd rowG5020
4th rowG5020
5th rowG5020

Common Values

ValueCountFrequency (%)
G502067142
96.8%
(Missing)2217
 
3.2%

Category Frequency Plot

2022-09-15T16:48:14.067613image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

FUNCSTAT
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing2217
Missing (%)3.2%
Memory size542.0 KiB
S
67142 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS
2nd rowS
3rd rowS
4th rowS
5th rowS

Common Values

ValueCountFrequency (%)
S67142
96.8%
(Missing)2217
 
3.2%

Category Frequency Plot

2022-09-15T16:48:14.094228image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

ALAND_right
Real number (ℝ≥0)

MISSING

Distinct1710
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean2223320.921
Minimum22158
Maximum277816097
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.125306image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum22158
5-th percentile266794
Q1577060
median1029660
Q32445029
95-th percentile7007313
Maximum277816097
Range277793939
Interquartile range (IQR)1867969

Descriptive statistics

Standard deviation4510131.45
Coefficient of variation (CV)2.028556205
Kurtosis509.0543551
Mean2223320.921
Median Absolute Deviation (MAD)647218
Skewness14.2356854
Sum1.492782133 × 1011
Variance2.03412857 × 1013
MonotonicityNot monotonic
2022-09-15T16:48:14.165216image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1084987310
 
0.4%
999706283
 
0.4%
1101771258
 
0.4%
656674219
 
0.3%
4896434208
 
0.3%
326475189
 
0.3%
472522182
 
0.3%
637446181
 
0.3%
624594179
 
0.3%
1277974174
 
0.3%
Other values (1700)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
2215827
< 0.1%
648275
 
< 0.1%
690949
 
< 0.1%
6987828
< 0.1%
8276912
< 0.1%
ValueCountFrequency (%)
2778160972
 
< 0.1%
949679386
< 0.1%
864373867
< 0.1%
799745927
< 0.1%
650068312
 
< 0.1%

AWATER_right
Real number (ℝ≥0)

MISSING
ZEROS

Distinct541
Distinct (%)0.8%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean59449.01951
Minimum0
Maximum5414806
Zeros52387
Zeros (%)75.5%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.204818image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile246111
Maximum5414806
Range5414806
Interquartile range (IQR)0

Descriptive statistics

Standard deviation282905.0034
Coefficient of variation (CV)4.758783336
Kurtosis101.4411721
Mean59449.01951
Median Absolute Deviation (MAD)0
Skewness9.037426985
Sum3991526068
Variance8.003524096 × 1010
MonotonicityNot monotonic
2022-09-15T16:48:14.247717image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
052387
75.5%
1126154310
 
0.4%
84111258
 
0.4%
143193139
 
0.2%
14139135
 
0.2%
466785126
 
0.2%
92402124
 
0.2%
143185123
 
0.2%
7945119
 
0.2%
161566117
 
0.2%
Other values (531)13304
 
19.2%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
052387
75.5%
421
 
< 0.1%
2622
 
< 0.1%
32476
 
0.1%
5333
 
< 0.1%
ValueCountFrequency (%)
54148062
 
< 0.1%
38561944
 
< 0.1%
380298384
0.1%
375179085
0.1%
34983389
 
< 0.1%

INTPTLAT
Real number (ℝ≥0)

MISSING

Distinct1710
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean41.84322643
Minimum41.3977129
Maximum42.2082668
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.288222image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum41.3977129
5-th percentile41.5858756
Q141.7478345
median41.858776
Q341.9466985
95-th percentile42.0655221
Maximum42.2082668
Range0.8105539
Interquartile range (IQR)0.198864

Descriptive statistics

Standard deviation0.1449551491
Coefficient of variation (CV)0.003464244073
Kurtosis-0.2453046713
Mean41.84322643
Median Absolute Deviation (MAD)0.1015047
Skewness-0.2595293475
Sum2809437.909
Variance0.02101199526
MonotonicityNot monotonic
2022-09-15T16:48:14.329976image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41.7572084310
 
0.4%
41.8917357283
 
0.4%
41.8809857258
 
0.4%
41.8990614219
 
0.3%
42.0113034208
 
0.3%
41.9727092189
 
0.3%
42.0159431182
 
0.3%
41.8767584181
 
0.3%
41.8836759179
 
0.3%
41.6997625174
 
0.3%
Other values (1700)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
41.39771291
 
< 0.1%
41.40432712
 
< 0.1%
41.40532481
 
< 0.1%
41.413359516
< 0.1%
41.41347372
 
< 0.1%
ValueCountFrequency (%)
42.20826681
 
< 0.1%
42.2068110
< 0.1%
42.20366631
 
< 0.1%
42.20323352
 
< 0.1%
42.20182461
 
< 0.1%

INTPTLON
Real number (ℝ)

MISSING

Distinct1710
Distinct (%)2.5%
Missing2217
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean-87.73575888
Minimum-88.4147251
Maximum-87.5294325
Zeros0
Zeros (%)0.0%
Negative67142
Negative (%)96.8%
Memory size542.0 KiB
2022-09-15T16:48:14.371904image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum-88.4147251
5-th percentile-88.00636521
Q1-87.7881169
median-87.7117002
Q3-87.6504857
95-th percentile-87.5804887
Maximum-87.5294325
Range0.8852926
Interquartile range (IQR)0.1376312

Descriptive statistics

Standard deviation0.1274813702
Coefficient of variation (CV)-0.001453014961
Kurtosis2.666553995
Mean-87.73575888
Median Absolute Deviation (MAD)0.06659
Skewness-1.443076616
Sum-5890754.322
Variance0.01625149976
MonotonicityNot monotonic
2022-09-15T16:48:14.412856image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-87.546555310
 
0.4%
-87.7186525283
 
0.4%
-87.6330703258
 
0.4%
-87.7213153219
 
0.3%
-87.7900018208
 
0.3%
-87.657341189
 
0.3%
-87.6665393182
 
0.3%
-87.7445832181
 
0.3%
-87.7698798179
 
0.3%
-87.6280536174
 
0.3%
Other values (1700)64959
93.7%
(Missing)2217
 
3.2%
ValueCountFrequency (%)
-88.41472512
 
< 0.1%
-88.34630311
 
< 0.1%
-88.32942741
 
< 0.1%
-88.32284813
 
< 0.1%
-88.316641610
< 0.1%
ValueCountFrequency (%)
-87.529432534
< 0.1%
-87.530702927
< 0.1%
-87.530871935
0.1%
-87.532407745
0.1%
-87.534899326
< 0.1%

GEOID
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean38.26854626
Minimum1
Maximum77
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.454013image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3
Q120
median39
Q360
95-th percentile73
Maximum77
Range76
Interquartile range (IQR)40

Descriptive statistics

Standard deviation22.79730848
Coefficient of variation (CV)0.5957192188
Kurtosis-1.220653044
Mean38.26854626
Median Absolute Deviation (MAD)20
Skewness0.05032785749
Sum1277251
Variance519.717274
MonotonicityNot monotonic
2022-09-15T16:48:14.495407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
252427
 
3.5%
681855
 
2.7%
231469
 
2.1%
431416
 
2.0%
291171
 
1.7%
491130
 
1.6%
711040
 
1.5%
31025
 
1.5%
61856
 
1.2%
44850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
1802
1.2%
2704
1.0%
31025
1.5%
4386
 
0.6%
5154
 
0.2%
ValueCountFrequency (%)
77676
1.0%
76265
 
0.4%
75333
0.5%
74168
 
0.2%
73491
0.7%

GEOG
Categorical

HIGH CARDINALITY
MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Memory size542.0 KiB
Austin
 
2427
Englewood
 
1855
Humboldt Park
 
1469
South Shore
 
1416
North Lawndale
 
1171
Other values (62)
25038 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO'Hare
2nd rowAuburn Gresham
3rd rowWest Pullman
4th rowLower West Side
5th rowChicago Lawn

Common Values

ValueCountFrequency (%)
Austin2427
 
3.5%
Englewood1855
 
2.7%
Humboldt Park1469
 
2.1%
South Shore1416
 
2.0%
North Lawndale1171
 
1.7%
Roseland1130
 
1.6%
Auburn Gresham1040
 
1.5%
Uptown1025
 
1.5%
New City856
 
1.2%
Chatham850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%

TOT_POP
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean45615.65397
Minimum2527
Maximum103050
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.537401image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2527
5-th percentile13418
Q126104
median41098
Q355931
95-th percentile96557
Maximum103050
Range100523
Interquartile range (IQR)29827

Descriptive statistics

Standard deviation23928.18281
Coefficient of variation (CV)0.5245607751
Kurtosis-0.1072502444
Mean45615.65397
Median Absolute Deviation (MAD)14994
Skewness0.7267350838
Sum1522468067
Variance572557932.4
MonotonicityNot monotonic
2022-09-15T16:48:14.578577image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
965572427
 
3.5%
243691855
 
2.7%
541651469
 
2.1%
539711416
 
2.0%
347941171
 
1.7%
388161130
 
1.6%
448781040
 
1.5%
571821025
 
1.5%
43628856
 
1.2%
31710850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
252761
 
0.1%
2567160
0.2%
6799117
0.2%
6820126
0.2%
7262175
0.3%
ValueCountFrequency (%)
103050590
 
0.9%
965572427
3.5%
87781284
 
0.4%
78116823
 
1.2%
77122704
 
1.0%

POP_HH
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean44981.8951
Minimum2527
Maximum102745
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.618627image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2527
5-th percentile13407
Q126087
median40539
Q353814
95-th percentile95481
Maximum102745
Range100218
Interquartile range (IQR)27727

Descriptive statistics

Standard deviation23656.01027
Coefficient of variation (CV)0.5259007033
Kurtosis-0.04941875817
Mean44981.8951
Median Absolute Deviation (MAD)14452
Skewness0.7512327988
Sum1501315731
Variance559606821.8
MonotonicityNot monotonic
2022-09-15T16:48:14.660441image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
954812427
 
3.5%
241931855
 
2.7%
538141469
 
2.1%
530421416
 
2.0%
342071171
 
1.7%
382571130
 
1.6%
447551040
 
1.5%
550821025
 
1.5%
43320856
 
1.2%
31708850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
252761
 
0.1%
2561160
0.2%
6799117
0.2%
6819126
0.2%
7248175
0.3%
ValueCountFrequency (%)
102745590
 
0.9%
954812427
3.5%
87279284
 
0.4%
77901823
 
1.2%
75531704
 
1.0%

POP_GQ
Real number (ℝ≥0)

MISSING

Distinct57
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean633.7588686
Minimum0
Maximum3386
Zeros178
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.700300image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q1123
median308
Q3929
95-th percentile2901
Maximum3386
Range3386
Interquartile range (IQR)806

Descriptive statistics

Standard deviation819.9751414
Coefficient of variation (CV)1.293828271
Kurtosis3.021714673
Mean633.7588686
Median Absolute Deviation (MAD)256
Skewness1.907950467
Sum21152336
Variance672359.2326
MonotonicityNot monotonic
2022-09-15T16:48:14.741604image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10762427
 
3.5%
3512030
 
2.9%
1761855
 
2.7%
5591583
 
2.3%
9291416
 
2.0%
5871171
 
1.7%
21106
 
1.6%
1231040
 
1.5%
21001025
 
1.5%
308856
 
1.2%
Other values (47)18867
27.2%
(Missing)35983
51.9%
ValueCountFrequency (%)
0178
 
0.3%
1776
1.1%
21106
1.6%
6160
 
0.2%
9216
 
0.3%
ValueCountFrequency (%)
3386802
1.2%
3031676
1.0%
2901243
 
0.4%
2798371
 
0.5%
21001025
1.5%

HISP
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean12884.15047
Minimum65
Maximum63967
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.782495image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum65
5-th percentile476
Q11598
median7587
Q319157
95-th percentile32949
Maximum63967
Range63902
Interquartile range (IQR)17559

Descriptive statistics

Standard deviation13688.44984
Coefficient of variation (CV)1.062425487
Kurtosis2.604405168
Mean12884.15047
Median Absolute Deviation (MAD)6833
Skewness1.467627347
Sum430021406
Variance187373658.9
MonotonicityNot monotonic
2022-09-15T16:48:14.822631image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185902427
 
3.5%
16051855
 
2.7%
317341469
 
2.1%
13521416
 
2.0%
40471171
 
1.7%
9261130
 
1.6%
16121040
 
1.5%
75871025
 
1.5%
29493856
 
1.2%
476850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
6561
 
0.1%
193209
0.3%
204117
 
0.2%
206175
0.3%
380320
0.5%
ValueCountFrequency (%)
63967823
1.2%
36756391
 
0.6%
36132393
 
0.6%
32949815
1.2%
317341469
2.1%

WHITE
Real number (ℝ≥0)

MISSING

Distinct66
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean10451.76474
Minimum4
Maximum77133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.863558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile168
Q1633
median3794
Q314608
95-th percentile36391
Maximum77133
Range77129
Interquartile range (IQR)13975

Descriptive statistics

Standard deviation15094.98023
Coefficient of variation (CV)1.444251818
Kurtosis5.676089618
Mean10451.76474
Median Absolute Deviation (MAD)3603
Skewness2.212789877
Sum348838100
Variance227858428.2
MonotonicityNot monotonic
2022-09-15T16:48:14.905938image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37942427
 
3.5%
1791972
 
2.8%
47751469
 
2.1%
9481416
 
2.0%
8351171
 
1.7%
2571130
 
1.6%
1911040
 
1.5%
298711025
 
1.5%
4168856
 
1.2%
168850
 
1.2%
Other values (56)20020
28.9%
(Missing)35983
51.9%
ValueCountFrequency (%)
461
 
0.1%
41175
 
0.3%
46209
0.3%
71160
 
0.2%
95491
0.7%
ValueCountFrequency (%)
77133590
0.9%
54446284
0.4%
54378371
0.5%
36391561
0.8%
30962676
1.0%

BLACK
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean18847.95047
Minimum62
Maximum72013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:14.947184image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile591
Q12633
median13649
Q323849
95-th percentile72013
Maximum72013
Range71951
Interquartile range (IQR)21216

Descriptive statistics

Standard deviation19935.32854
Coefficient of variation (CV)1.057692112
Kurtosis1.207208446
Mean18847.95047
Median Absolute Deviation (MAD)11016
Skewness1.386865175
Sum629069195
Variance397417324.1
MonotonicityNot monotonic
2022-09-15T16:48:14.988172image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
720132427
 
3.5%
219411855
 
2.7%
161461469
 
2.1%
498111416
 
2.0%
291111171
 
1.7%
366261130
 
1.6%
420591040
 
1.5%
108001025
 
1.5%
8142856
 
1.2%
30275850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
6293
 
0.1%
124152
 
0.2%
279176
0.3%
363429
0.6%
385265
0.4%
ValueCountFrequency (%)
720132427
3.5%
498111416
2.0%
420591040
1.5%
366261130
1.6%
30275850
 
1.2%

ASIAN
Real number (ℝ≥0)

MISSING

Distinct66
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean2111.493229
Minimum4
Maximum19815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.029274image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile25
Q159
median369
Q33098
95-th percentile7717
Maximum19815
Range19811
Interquartile range (IQR)3039

Descriptive statistics

Standard deviation3622.409166
Coefficient of variation (CV)1.715567503
Kurtosis10.54701897
Mean2111.493229
Median Absolute Deviation (MAD)342
Skewness2.969030529
Sum70473198
Variance13121848.17
MonotonicityNot monotonic
2022-09-15T16:48:15.072012image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3692427
 
3.5%
271855
 
2.7%
4291469
 
2.1%
1481416
 
2.0%
1051171
 
1.7%
471130
 
1.6%
431040
 
1.5%
61821025
 
1.5%
1214856
 
1.2%
39850
 
1.2%
Other values (56)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
461
 
0.1%
6175
0.3%
8126
 
0.2%
15160
0.2%
16320
0.5%
ValueCountFrequency (%)
19815704
1.0%
14176291
0.4%
1003394
 
0.1%
7717590
0.9%
7316676
1.0%

OTHER
Real number (ℝ≥0)

MISSING

Distinct66
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean1320.295062
Minimum68
Maximum4943
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.112395image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum68
5-th percentile277
Q1626
median960
Q31791
95-th percentile3122
Maximum4943
Range4875
Interquartile range (IQR)1165

Descriptive statistics

Standard deviation994.2294636
Coefficient of variation (CV)0.7530358114
Kurtosis1.847176467
Mean1320.295062
Median Absolute Deviation (MAD)415
Skewness1.405161228
Sum44066168
Variance988492.2262
MonotonicityNot monotonic
2022-09-15T16:48:15.154698image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
17912427
 
3.5%
6171855
 
2.7%
10811469
 
2.1%
17121416
 
2.0%
6961171
 
1.7%
9601130
 
1.6%
9731040
 
1.5%
27421025
 
1.5%
611856
 
1.2%
752850
 
1.2%
Other values (56)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
6861
 
0.1%
84160
0.2%
135152
0.2%
144176
0.3%
171126
0.2%
ValueCountFrequency (%)
4943590
0.9%
3947284
 
0.4%
3304704
1.0%
3122371
0.5%
3110802
1.2%

HU_TOT
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean20441.37033
Minimum1192
Maximum61920
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.194454image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1192
5-th percentile5918
Q112626
median17159
Q328249
95-th percentile39477
Maximum61920
Range60728
Interquartile range (IQR)15623

Descriptive statistics

Standard deviation11547.39376
Coefficient of variation (CV)0.5649031144
Kurtosis1.356165777
Mean20441.37033
Median Absolute Deviation (MAD)6091
Skewness1.088982104
Sum682251176
Variance133342302.7
MonotonicityNot monotonic
2022-09-15T16:48:15.234708image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394772427
 
3.5%
126261855
 
2.7%
212061469
 
2.1%
302251416
 
2.0%
151931171
 
1.7%
173811130
 
1.6%
206641040
 
1.5%
350191025
 
1.5%
15959856
 
1.2%
17159850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
119261
 
0.1%
1465160
0.2%
2799175
0.3%
3442117
0.2%
3501126
0.2%
ValueCountFrequency (%)
61920590
 
0.9%
46174284
 
0.4%
394772427
3.5%
38649371
 
0.5%
350191025
1.5%

TOT_HH
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean18434.29464
Minimum1036
Maximum57721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.274884image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1036
5-th percentile5168
Q110353
median15080
Q325748
95-th percentile35864
Maximum57721
Range56685
Interquartile range (IQR)15395

Descriptive statistics

Standard deviation10734.80398
Coefficient of variation (CV)0.5823278943
Kurtosis1.543332776
Mean18434.29464
Median Absolute Deviation (MAD)5483
Skewness1.148832913
Sum615263018
Variance115236016.5
MonotonicityNot monotonic
2022-09-15T16:48:15.315993image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
358642427
 
3.5%
95971855
 
2.7%
190721469
 
2.1%
257481416
 
2.0%
128381171
 
1.7%
150801130
 
1.6%
180711040
 
1.5%
322151025
 
1.5%
13813856
 
1.2%
15053850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
103661
 
0.1%
1140160
0.2%
2523175
0.3%
2995126
0.2%
3217117
0.2%
ValueCountFrequency (%)
57721590
 
0.9%
42920284
 
0.4%
358642427
3.5%
35570371
 
0.5%
322151025
1.5%

VAC_HU
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean2007.075683
Minimum156
Maximum4477
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.357297image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum156
5-th percentile402
Q11137
median2106
Q32750
95-th percentile4199
Maximum4477
Range4321
Interquartile range (IQR)1613

Descriptive statistics

Standard deviation1120.421403
Coefficient of variation (CV)0.5582357516
Kurtosis-0.5963108911
Mean2007.075683
Median Absolute Deviation (MAD)818
Skewness0.3213050107
Sum66988158
Variance1255344.119
MonotonicityNot monotonic
2022-09-15T16:48:15.397004image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36132427
 
3.5%
30291855
 
2.7%
21341469
 
2.1%
44771416
 
2.0%
23551171
 
1.7%
23011130
 
1.6%
25931040
 
1.5%
28041025
 
1.5%
2146856
 
1.2%
2106850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
15661
 
0.1%
225117
0.2%
22793
0.1%
238188
0.3%
242152
0.2%
ValueCountFrequency (%)
44771416
2.0%
4199590
 
0.9%
36132427
3.5%
3254284
 
0.4%
3079371
 
0.5%

HH_SIZE
Real number (ℝ≥0)

MISSING

Distinct67
Distinct (%)0.2%
Missing35983
Missing (%)51.9%
Infinite0
Infinite (%)0.0%
Mean2.529599404
Minimum1.709824616
Maximum3.816091954
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.436055image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1.709824616
5-th percentile1.748342414
Q12.177167912
median2.524281346
Q32.74273061
95-th percentile3.322004264
Maximum3.816091954
Range2.106267338
Interquartile range (IQR)0.5655626984

Descriptive statistics

Standard deviation0.4528095715
Coefficient of variation (CV)0.1790044585
Kurtosis-0.02404916221
Mean2.529599404
Median Absolute Deviation (MAD)0.2973419766
Skewness0.2600347568
Sum84427.90969
Variance0.205036508
MonotonicityNot monotonic
2022-09-15T16:48:15.476078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2.6623076072427
 
3.5%
2.5208919451855
 
2.7%
2.8216233221469
 
2.1%
2.0600434991416
 
2.0%
2.6645116061171
 
1.7%
2.536936341130
 
1.6%
2.4766199991040
 
1.5%
1.7098246161025
 
1.5%
3.136176066856
 
1.2%
2.106423969850
 
1.2%
Other values (57)20137
29.0%
(Missing)35983
51.9%
ValueCountFrequency (%)
1.7098246161025
1.5%
1.748342414676
1.0%
1.780028066590
0.9%
1.792077203243
 
0.4%
1.80404463270
 
0.4%
ValueCountFrequency (%)
3.816091954393
0.6%
3.635114669269
 
0.4%
3.495435527176
 
0.3%
3.403314917152
 
0.2%
3.322004264823
1.2%

index_right
Real number (ℝ≥0)

MISSING

Distinct34488
Distinct (%)51.4%
Missing2227
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean291019.7574
Minimum31
Maximum535141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.909205image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile21414.6
Q1191179.25
median278167
Q3508418.25
95-th percentile515797
Maximum535141
Range535110
Interquartile range (IQR)317239

Descriptive statistics

Standard deviation167876.3372
Coefficient of variation (CV)0.5768554641
Kurtosis-1.165378547
Mean291019.7574
Median Absolute Deviation (MAD)171944
Skewness-0.07273084222
Sum1.953673835 × 1010
Variance2.818246459 × 1010
MonotonicityNot monotonic
2022-09-15T16:48:15.951393image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
514198113
 
0.2%
515834108
 
0.2%
515839105
 
0.2%
51213899
 
0.1%
51577097
 
0.1%
51586093
 
0.1%
51576192
 
0.1%
51581489
 
0.1%
51576085
 
0.1%
51412982
 
0.1%
Other values (34478)66169
95.4%
(Missing)2227
 
3.2%
ValueCountFrequency (%)
311
< 0.1%
361
< 0.1%
421
< 0.1%
451
< 0.1%
471
< 0.1%
ValueCountFrequency (%)
5351412
< 0.1%
5351371
< 0.1%
5351351
< 0.1%
5351151
< 0.1%
5351122
< 0.1%

FIRST_COUN
Real number (ℝ≥0)

MISSING

Distinct7
Distinct (%)< 0.1%
Missing2227
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean32.92417923
Minimum31
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:15.983143image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile31
Q131
median31
Q331
95-th percentile31
Maximum197
Range166
Interquartile range (IQR)0

Descriptive statistics

Standard deviation15.97700325
Coefficient of variation (CV)0.4852665617
Kurtosis91.42881863
Mean32.92417923
Median Absolute Deviation (MAD)0
Skewness9.443171448
Sum2210266
Variance255.2646329
MonotonicityNot monotonic
2022-09-15T16:48:16.012690image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
3165498
94.4%
43630
 
0.9%
197560
 
0.8%
97266
 
0.4%
89124
 
0.2%
11131
 
< 0.1%
9323
 
< 0.1%
(Missing)2227
 
3.2%
ValueCountFrequency (%)
3165498
94.4%
43630
 
0.9%
89124
 
0.2%
9323
 
< 0.1%
97266
 
0.4%
ValueCountFrequency (%)
197560
0.8%
11131
 
< 0.1%
97266
0.4%
9323
 
< 0.1%
89124
 
0.2%

LANDUSE
Real number (ℝ≥0)

MISSING

Distinct55
Distinct (%)0.1%
Missing2227
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean2421.354585
Minimum1111
Maximum9999
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.050558image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1111
5-th percentile1111
Q11112
median1130
Q36000
95-th percentile6000
Maximum9999
Range8888
Interquartile range (IQR)4888

Descriptive statistics

Standard deviation2112.226657
Coefficient of variation (CV)0.8723326481
Kurtosis-0.7796051676
Mean2421.354585
Median Absolute Deviation (MAD)19
Skewness1.089120284
Sum162550376
Variance4461501.451
MonotonicityNot monotonic
2022-09-15T16:48:16.089625image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
113020009
28.8%
600017087
24.6%
111116718
24.1%
13103893
 
5.6%
11121689
 
2.4%
12151578
 
2.3%
12161552
 
2.2%
1250721
 
1.0%
1140377
 
0.5%
3100349
 
0.5%
Other values (45)3159
 
4.6%
(Missing)2227
 
3.2%
ValueCountFrequency (%)
111116718
24.1%
11121689
 
2.4%
113020009
28.8%
1140377
 
0.5%
1151117
 
0.2%
ValueCountFrequency (%)
999910
 
< 0.1%
600017087
24.6%
50009
 
< 0.1%
424026
 
< 0.1%
42304
 
< 0.1%

LANDUSE2
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing69294
Missing (%)99.9%
Memory size542.0 KiB

OS_MGMT
Categorical

MISSING

Distinct4
Distinct (%)0.8%
Missing68862
Missing (%)99.3%
Memory size542.0 KiB
MUNI
356 
CNTY
96 
XXXX
44 
STA
 
1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowMUNI
2nd rowCNTY
3rd rowMUNI
4th rowMUNI
5th rowCNTY

Common Values

ValueCountFrequency (%)
MUNI356
 
0.5%
CNTY96
 
0.1%
XXXX44
 
0.1%
STA1
 
< 0.1%
(Missing)68862
99.3%

Category Frequency Plot

2022-09-15T16:48:16.125353image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

FAC_NAME
Categorical

MISSING

Distinct35
Distinct (%)17.2%
Missing69155
Missing (%)99.7%
Memory size542.0 KiB
O'Hare International Airport
123 
Midway International Airport
 
12
University of Illinois at Chicago
 
9
The University of Chicago
 
6
Northwestern University
 
6
Other values (30)
48 

Unique

Unique19 ?
Unique (%)9.3%

Sample

1st rowO'Hare International Airport
2nd rowO'Hare International Airport
3rd rowMidway International Airport
4th rowO'Hare International Airport
5th rowNorth Riverside Park Mall

Common Values

ValueCountFrequency (%)
O'Hare International Airport123
 
0.2%
Midway International Airport12
 
< 0.1%
University of Illinois at Chicago9
 
< 0.1%
The University of Chicago6
 
< 0.1%
Northwestern University6
 
< 0.1%
Woodfield Mall5
 
< 0.1%
Loyola University Chicago4
 
< 0.1%
Moraine Valley Community College3
 
< 0.1%
Randhurst Village3
 
< 0.1%
River Oaks Center2
 
< 0.1%
Other values (25)31
 
< 0.1%
(Missing)69155
99.7%

PLATTED
Categorical

CONSTANT
MISSING
REJECTED

Distinct1
Distinct (%)12.5%
Missing69351
Missing (%)> 99.9%
Memory size542.0 KiB
O

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowO
3rd rowO
4th rowO
5th rowO

Common Values

ValueCountFrequency (%)
O8
 
< 0.1%
(Missing)69351
> 99.9%

Category Frequency Plot

2022-09-15T16:48:16.156113image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

MODIFIER
Categorical

MISSING

Distinct3
Distinct (%)4.5%
Missing69293
Missing (%)99.9%
Memory size542.0 KiB
M
61 
S
 
3
T
 
2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowS
3rd rowM
4th rowM
5th rowM

Common Values

ValueCountFrequency (%)
M61
 
0.1%
S3
 
< 0.1%
T2
 
< 0.1%
(Missing)69293
99.9%

Category Frequency Plot

2022-09-15T16:48:16.184624image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Shape_Leng
Real number (ℝ≥0)

MISSING

Distinct34488
Distinct (%)51.4%
Missing2227
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean23067.93267
Minimum99.82532036
Maximum159346.3177
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.217407image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum99.82532036
5-th percentile342.5411267
Q1669.5021714
median1498.353985
Q313344.43094
95-th percentile129391.792
Maximum159346.3177
Range159246.4923
Interquartile range (IQR)12674.92877

Descriptive statistics

Standard deviation42167.15901
Coefficient of variation (CV)1.8279557
Kurtosis1.760996096
Mean23067.93267
Median Absolute Deviation (MAD)1072.061199
Skewness1.793910602
Sum1548596456
Variance1778069299
MonotonicityNot monotonic
2022-09-15T16:48:16.258685image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44541.19513113
 
0.2%
133463.8037108
 
0.2%
87553.28292105
 
0.2%
148759.436999
 
0.1%
112750.121297
 
0.1%
98898.3054693
 
0.1%
133198.21892
 
0.1%
108646.523489
 
0.1%
129646.025385
 
0.1%
145763.417782
 
0.1%
Other values (34478)66169
95.4%
(Missing)2227
 
3.2%
ValueCountFrequency (%)
99.825320361
< 0.1%
120.92424092
< 0.1%
135.54704341
< 0.1%
140.18346311
< 0.1%
146.66230212
< 0.1%
ValueCountFrequency (%)
159346.317727
< 0.1%
157730.720613
< 0.1%
154794.780124
< 0.1%
154609.34244
 
< 0.1%
153104.722211
< 0.1%

Shape_Area
Real number (ℝ≥0)

MISSING
SKEWED

Distinct34488
Distinct (%)51.4%
Missing2227
Missing (%)3.2%
Infinite0
Infinite (%)0.0%
Mean1027691.687
Minimum310.3285327
Maximum187847552
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.299953image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum310.3285327
5-th percentile5882.322443
Q125405.75035
median93042.87558
Q31092945.061
95-th percentile3445158.916
Maximum187847552
Range187847241.7
Interquartile range (IQR)1067539.31

Descriptive statistics

Standard deviation6632856.701
Coefficient of variation (CV)6.454130926
Kurtosis741.3285162
Mean1027691.687
Median Absolute Deviation (MAD)85483.77507
Skewness26.60461822
Sum6.899099835 × 1010
Variance4.399478802 × 1013
MonotonicityNot monotonic
2022-09-15T16:48:16.341585image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1401847.179113
 
0.2%
4218393.9108
 
0.2%
3526102.795105
 
0.2%
3660653.75199
 
0.1%
3574808.46197
 
0.1%
2823024.95493
 
0.1%
3374725.75492
 
0.1%
4682848.46689
 
0.1%
3381264.59285
 
0.1%
3581352.09282
 
0.1%
Other values (34478)66169
95.4%
(Missing)2227
 
3.2%
ValueCountFrequency (%)
310.32853271
< 0.1%
595.33774581
< 0.1%
888.39194921
< 0.1%
905.95839612
< 0.1%
1028.1723961
< 0.1%
ValueCountFrequency (%)
18784755279
0.1%
88016592.168
 
< 0.1%
28617937.4811
 
< 0.1%
27777436.071
 
< 0.1%
27402973.751
 
< 0.1%

landuse_name
Categorical

HIGH CARDINALITY
MISSING

Distinct55
Distinct (%)0.1%
Missing2227
Missing (%)3.2%
Memory size542.0 KiB
Multi-Family
20009 
NON-PARCEL AREAS
17087 
Single-Family Detached
16718 
Medical Facilities
3893 
Single-Family Attached
 
1689
Other values (50)
7736 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowAircraft Transportation
2nd rowNON-PARCEL AREAS
3rd rowNON-PARCEL AREAS
4th rowSingle-Family Detached
5th rowMobile Home Parks and Trailer Courts

Common Values

ValueCountFrequency (%)
Multi-Family20009
28.8%
NON-PARCEL AREAS17087
24.6%
Single-Family Detached16718
24.1%
Medical Facilities3893
 
5.6%
Single-Family Attached1689
 
2.4%
Urban Mix1578
 
2.3%
Urban Mix w/Residential Component1552
 
2.2%
Hotel/Motel721
 
1.0%
Mobile Home Parks and Trailer Courts377
 
0.5%
Open Space - Primarily Recreation349
 
0.5%
Other values (45)3159
 
4.6%
(Missing)2227
 
3.2%

landuse_sub_name
Categorical

MISSING

Distinct15
Distinct (%)< 0.1%
Missing2227
Missing (%)3.2%
Memory size542.0 KiB
Residential
38910 
Non-Parcel Areas
17087 
Institutional
4551 
Commercial
4432 
TRANS/COMM/UTIL/WASTE
 
799
Other values (10)
 
1353

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowTRANS/COMM/UTIL/WASTE
2nd rowNon-Parcel Areas
3rd rowNon-Parcel Areas
4th rowResidential
5th rowResidential

Common Values

ValueCountFrequency (%)
Residential38910
56.1%
Non-Parcel Areas17087
24.6%
Institutional4551
 
6.6%
Commercial4432
 
6.4%
TRANS/COMM/UTIL/WASTE799
 
1.2%
Industrial478
 
0.7%
Primarily Recreation349
 
0.5%
Vacant/Undeveloped Land266
 
0.4%
Primarily Conservation93
 
0.1%
Golf Course55
 
0.1%
Other values (5)112
 
0.2%
(Missing)2227
 
3.2%

landuse_major_name
Categorical

MISSING

Distinct7
Distinct (%)< 0.1%
Missing2227
Missing (%)3.2%
Memory size542.0 KiB
Urbanized
49170 
Non-Parcel Areas
17087 
Open Space
 
508
Vacant/Under Construction
 
310
AGRICULTURE
 
38
Other values (2)
 
19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowUrbanized
2nd rowNon-Parcel Areas
3rd rowNon-Parcel Areas
4th rowUrbanized
5th rowUrbanized

Common Values

ValueCountFrequency (%)
Urbanized49170
70.9%
Non-Parcel Areas17087
 
24.6%
Open Space508
 
0.7%
Vacant/Under Construction310
 
0.4%
AGRICULTURE38
 
0.1%
Not Classifiable10
 
< 0.1%
Water9
 
< 0.1%
(Missing)2227
 
3.2%

Category Frequency Plot

2022-09-15T16:48:16.384529image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

death_street
Categorical

HIGH CARDINALITY
MISSING

Distinct40373
Distinct (%)67.2%
Missing9314
Missing (%)13.4%
Memory size542.0 KiB
4440 West 95th Street
 
880
1775 Dempster Street
 
720
5841 South Maryland Avenue
 
698
2100 Pfingsten Road
 
548
2160 South 1st Avenue
 
487
Other values (40368)
56712 

Unique

Unique38750 ?
Unique (%)64.5%

Sample

1st row7435 West Talcott Avenue
2nd row225 East Chicago Avenue
3rd row499 E. North Water St.
4th row1317 PORTLAND
5th row8759 PELIKIN

Common Values

ValueCountFrequency (%)
4440 West 95th Street880
 
1.3%
1775 Dempster Street720
 
1.0%
5841 South Maryland Avenue698
 
1.0%
2100 Pfingsten Road548
 
0.8%
2160 South 1st Avenue487
 
0.7%
1 Ingalls Drive 447
 
0.6%
12251 South 80th Avenue437
 
0.6%
1500 South Fairfield Avenue 412
 
0.6%
7435 West Talcott Avenue380
 
0.5%
4440 W 95TH ST362
 
0.5%
Other values (40363)54674
78.8%
(Missing)9314
 
13.4%

death_city
Categorical

HIGH CARDINALITY
MISSING

Distinct297
Distinct (%)0.5%
Missing9635
Missing (%)13.9%
Memory size542.0 KiB
Chicago
34292 
Oak Lawn
 
2331
Maywood
 
1243
Park Ridge
 
1057
Evanston
 
1014
Other values (292)
19787 

Unique

Unique75 ?
Unique (%)0.1%

Sample

1st rowChicago
2nd rowChicago
3rd rowChicago
4th rowChicago
5th rowChicago

Common Values

ValueCountFrequency (%)
Chicago34292
49.4%
Oak Lawn2331
 
3.4%
Maywood1243
 
1.8%
Park Ridge1057
 
1.5%
Evanston1014
 
1.5%
Arlington Heights893
 
1.3%
Glenview845
 
1.2%
Harvey840
 
1.2%
Berwyn821
 
1.2%
Oak Park775
 
1.1%
Other values (287)15613
22.5%
(Missing)9635
 
13.9%

death_county
Categorical

MISSING

Distinct17
Distinct (%)< 0.1%
Missing35330
Missing (%)50.9%
Memory size542.0 KiB
Cook County
33879 
Du Page County
 
79
Will County
 
17
Lake County
 
16
Lake County/Indiana
 
10
Other values (12)
 
28

Unique

Unique6 ?
Unique (%)< 0.1%

Sample

1st rowCook County
2nd rowCook County
3rd rowCook County
4th rowCook County
5th rowCook County

Common Values

ValueCountFrequency (%)
Cook County33879
48.8%
Du Page County79
 
0.1%
Will County17
 
< 0.1%
Lake County16
 
< 0.1%
Lake County/Indiana10
 
< 0.1%
Kane County7
 
< 0.1%
Cook6
 
< 0.1%
McHenry County3
 
< 0.1%
La Porte2
 
< 0.1%
Kendall2
 
< 0.1%
Other values (7)8
 
< 0.1%
(Missing)35330
50.9%

death_state
Categorical

MISSING

Distinct9
Distinct (%)< 0.1%
Missing9828
Missing (%)14.2%
Memory size542.0 KiB
IL
59455 
IN
 
61
GA
 
7
MI
 
2
WI
 
2
Other values (4)
 
4

Unique

Unique4 ?
Unique (%)< 0.1%

Sample

1st rowIL
2nd rowIL
3rd rowIL
4th rowIL
5th rowIL

Common Values

ValueCountFrequency (%)
IL 59455
85.7%
IN 61
 
0.1%
GA 7
 
< 0.1%
MI 2
 
< 0.1%
WI 2
 
< 0.1%
MN 1
 
< 0.1%
OK 1
 
< 0.1%
TX 1
 
< 0.1%
IA 1
 
< 0.1%
(Missing)9828
 
14.2%

Category Frequency Plot

2022-09-15T16:48:16.425819image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

death_zip
Unsupported

MISSING
REJECTED
UNSUPPORTED

Missing10761
Missing (%)15.5%
Memory size542.0 KiB

death_location
Categorical

HIGH CARDINALITY
MISSING

Distinct5890
Distinct (%)15.9%
Missing32243
Missing (%)46.5%
Memory size542.0 KiB
RESIDENCE
 
2574
Residence
 
2410
HOSPITAL ICU
 
1311
HOSPITAL
 
1270
ER
 
1157
Other values (5885)
28394 

Unique

Unique4125 ?
Unique (%)11.1%

Sample

1st rowInpatient
2nd rowICU-HOSPITAL
3rd rowGARAGE
4th rowresidence
5th rowresidence

Common Values

ValueCountFrequency (%)
RESIDENCE2574
 
3.7%
Residence2410
 
3.5%
HOSPITAL ICU1311
 
1.9%
HOSPITAL1270
 
1.8%
ER1157
 
1.7%
Hospital1075
 
1.5%
SCENE1056
 
1.5%
HOSPITAL ER987
 
1.4%
Hospital ER727
 
1.0%
residence682
 
1.0%
Other values (5880)23867
34.4%
(Missing)32243
46.5%

death_location_1
Categorical

HIGH CARDINALITY
MISSING

Distinct152
Distinct (%)0.3%
Missing14487
Missing (%)20.9%
Memory size542.0 KiB
Hospital
17236 
Residence
7354 
Hospital-ER
6257 
Scene
5463 
Bedroom
2467 
Other values (147)
16095 

Unique

Unique30 ?
Unique (%)0.1%

Sample

1st rowHospital
2nd rowHospital
3rd rowRiver
4th rowGarage
5th rowResidence

Common Values

ValueCountFrequency (%)
Hospital17236
24.9%
Residence7354
10.6%
Hospital-ER6257
 
9.0%
Scene5463
 
7.9%
Bedroom2467
 
3.6%
Apartment2350
 
3.4%
Emergency Room1489
 
2.1%
Nursing Home1275
 
1.8%
Hospice1269
 
1.8%
Decedent's Home1146
 
1.7%
Other values (142)8566
12.4%
(Missing)14487
20.9%

incident_matches_death
Real number (ℝ≥0)

ZEROS

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.00350351072
Minimum0
Maximum1
Zeros69116
Zeros (%)99.6%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.455995image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.05908710916
Coefficient of variation (CV)16.86511442
Kurtosis280.4518029
Mean0.00350351072
Median Absolute Deviation (MAD)0
Skewness16.80606188
Sum243
Variance0.003491286469
MonotonicityNot monotonic
2022-09-15T16:48:16.484071image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
069116
99.6%
1243
 
0.4%
ValueCountFrequency (%)
069116
99.6%
1243
 
0.4%
ValueCountFrequency (%)
1243
 
0.4%
069116
99.6%

death_datetime
Categorical

HIGH CARDINALITY

Distinct68006
Distinct (%)98.1%
Missing61
Missing (%)0.1%
Memory size542.0 KiB
2018-08-26 04:09:00
 
7
2016-02-04 13:53:00
 
6
2019-04-19 10:45:00
 
5
2022-01-18 14:15:00
 
4
2017-03-30 16:32:00
 
4
Other values (68001)
69272 

Unique

Unique66776 ?
Unique (%)96.4%

Sample

1st row2020-05-15 22:52:00
2nd row2021-04-09 15:55:00
3rd row2014-09-21 13:50:00
4th row2014-09-22 16:55:00
5th row2014-09-27 17:10:00

Common Values

ValueCountFrequency (%)
2018-08-26 04:09:007
 
< 0.1%
2016-02-04 13:53:006
 
< 0.1%
2019-04-19 10:45:005
 
< 0.1%
2022-01-18 14:15:004
 
< 0.1%
2017-03-30 16:32:004
 
< 0.1%
2022-03-09 02:22:004
 
< 0.1%
2022-01-10 14:50:003
 
< 0.1%
2022-02-02 11:55:003
 
< 0.1%
2020-12-19 20:20:003
 
< 0.1%
2015-07-17 17:33:003
 
< 0.1%
Other values (67996)69256
99.9%
(Missing)61
 
0.1%

death_time
Categorical

HIGH CARDINALITY

Distinct1440
Distinct (%)2.1%
Missing61
Missing (%)0.1%
Memory size542.0 KiB
00:00:00
 
255
12:30:00
 
153
17:00:00
 
148
16:00:00
 
142
11:30:00
 
139
Other values (1435)
68461 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22:52:00
2nd row15:55:00
3rd row13:50:00
4th row16:55:00
5th row17:10:00

Common Values

ValueCountFrequency (%)
00:00:00255
 
0.4%
12:30:00153
 
0.2%
17:00:00148
 
0.2%
16:00:00142
 
0.2%
11:30:00139
 
0.2%
13:30:00137
 
0.2%
14:00:00137
 
0.2%
15:30:00136
 
0.2%
13:00:00131
 
0.2%
16:45:00130
 
0.2%
Other values (1430)67790
97.7%

death_year
Real number (ℝ≥0)

Distinct12
Distinct (%)< 0.1%
Missing61
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean2018.913619
Minimum2008
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.513483image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum2008
5-th percentile2015
Q12017
median2020
Q32021
95-th percentile2022
Maximum2022
Range14
Interquartile range (IQR)4

Descriptive statistics

Standard deviation2.309266496
Coefficient of variation (CV)0.001143816394
Kurtosis-0.9009193185
Mean2018.913619
Median Absolute Deviation (MAD)1
Skewness-0.5119083933
Sum139906676
Variance5.332711748
MonotonicityNot monotonic
2022-09-15T16:48:16.544568image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
202016079
23.2%
202112611
18.2%
20227874
11.4%
20166316
 
9.1%
20196272
 
9.0%
20186189
 
8.9%
20176126
 
8.8%
20155650
 
8.1%
20142175
 
3.1%
20133
 
< 0.1%
Other values (2)3
 
< 0.1%
(Missing)61
 
0.1%
ValueCountFrequency (%)
20081
 
< 0.1%
20112
 
< 0.1%
20133
 
< 0.1%
20142175
 
3.1%
20155650
8.1%
ValueCountFrequency (%)
20227874
11.4%
202112611
18.2%
202016079
23.2%
20196272
 
9.0%
20186189
 
8.9%

death_month
Real number (ℝ≥0)

Distinct12
Distinct (%)< 0.1%
Missing61
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean6.441109412
Minimum1
Maximum12
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.576063image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q14
median6
Q310
95-th percentile12
Maximum12
Range11
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.551277644
Coefficient of variation (CV)0.5513456482
Kurtosis-1.227511505
Mean6.441109412
Median Absolute Deviation (MAD)3
Skewness0.0471931054
Sum446356
Variance12.6115729
MonotonicityNot monotonic
2022-09-15T16:48:16.606101image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
17329
10.6%
57039
10.1%
126996
10.1%
46375
9.2%
115778
8.3%
65487
7.9%
85233
7.5%
95134
7.4%
75115
7.4%
25026
7.2%
Other values (2)9786
14.1%
ValueCountFrequency (%)
17329
10.6%
25026
7.2%
34841
7.0%
46375
9.2%
57039
10.1%
ValueCountFrequency (%)
126996
10.1%
115778
8.3%
104945
7.1%
95134
7.4%
85233
7.5%

death_day
Real number (ℝ≥0)

Distinct31
Distinct (%)< 0.1%
Missing61
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean15.54610523
Minimum1
Maximum31
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.639347image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q18
median15
Q323
95-th percentile29
Maximum31
Range30
Interquartile range (IQR)15

Descriptive statistics

Standard deviation8.856672195
Coefficient of variation (CV)0.5697036052
Kurtosis-1.20536843
Mean15.54610523
Median Absolute Deviation (MAD)8
Skewness0.02737915271
Sum1077314
Variance78.44064236
MonotonicityNot monotonic
2022-09-15T16:48:16.674338image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
22439
 
3.5%
32435
 
3.5%
12412
 
3.5%
42407
 
3.5%
82345
 
3.4%
52331
 
3.4%
62322
 
3.3%
232321
 
3.3%
242288
 
3.3%
192286
 
3.3%
Other values (21)45712
65.9%
ValueCountFrequency (%)
12412
3.5%
22439
3.5%
32435
3.5%
42407
3.5%
52331
3.4%
ValueCountFrequency (%)
311384
2.0%
302064
3.0%
292048
3.0%
282155
3.1%
272197
3.2%

death_week
Real number (ℝ≥0)

Distinct53
Distinct (%)0.1%
Missing61
Missing (%)0.1%
Infinite0
Infinite (%)0.0%
Mean26.44437069
Minimum1
Maximum53
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.711459image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q114
median25
Q340
95-th percentile51
Maximum53
Range52
Interquartile range (IQR)26

Descriptive statistics

Standard deviation15.58815596
Coefficient of variation (CV)0.5894697268
Kurtosis-1.211063028
Mean26.44437069
Median Absolute Deviation (MAD)13
Skewness0.05099459003
Sum1832542
Variance242.9906064
MonotonicityNot monotonic
2022-09-15T16:48:16.753774image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11796
 
2.6%
521732
 
2.5%
21712
 
2.5%
181698
 
2.4%
191661
 
2.4%
201627
 
2.3%
31616
 
2.3%
511608
 
2.3%
491586
 
2.3%
161541
 
2.2%
Other values (43)52721
76.0%
ValueCountFrequency (%)
11796
2.6%
21712
2.5%
31616
2.3%
41471
2.1%
51392
2.0%
ValueCountFrequency (%)
53604
 
0.9%
521732
2.5%
511608
2.3%
501514
2.2%
491586
2.3%
Distinct7
Distinct (%)< 0.1%
Missing61
Missing (%)0.1%
Memory size542.0 KiB
Monday
10327 
Sunday
10124 
Friday
9989 
Tuesday
9875 
Saturday
9866 
Other values (2)
19117 

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFriday
2nd rowFriday
3rd rowSunday
4th rowMonday
5th rowSaturday

Common Values

ValueCountFrequency (%)
Monday10327
14.9%
Sunday10124
14.6%
Friday9989
14.4%
Tuesday9875
14.2%
Saturday9866
14.2%
Wednesday9672
13.9%
Thursday9445
13.6%
(Missing)61
 
0.1%

Category Frequency Plot

2022-09-15T16:48:16.795732image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

hotel
Real number (ℝ≥0)

ZEROS

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.009256188815
Minimum0
Maximum1
Zeros68717
Zeros (%)99.1%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.825714image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.09576347949
Coefficient of variation (CV)10.34588656
Kurtosis103.0526835
Mean0.009256188815
Median Absolute Deviation (MAD)0
Skewness10.24937617
Sum642
Variance0.009170644003
MonotonicityNot monotonic
2022-09-15T16:48:16.854245image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
068717
99.1%
1642
 
0.9%
ValueCountFrequency (%)
068717
99.1%
1642
 
0.9%
ValueCountFrequency (%)
1642
 
0.9%
068717
99.1%

hot
Real number (ℝ≥0)

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.881107image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum69359
Variance0
MonotonicityIncreasing
2022-09-15T16:48:16.907714image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
169359
100.0%
ValueCountFrequency (%)
169359
100.0%
ValueCountFrequency (%)
169359
100.0%

cold
Real number (ℝ≥0)

CONSTANT
REJECTED

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1
Minimum1
Maximum1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.934263image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile1
Maximum1
Range0
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0
Coefficient of variation (CV)0
Kurtosis0
Mean1
Median Absolute Deviation (MAD)0
Skewness0
Sum69359
Variance0
MonotonicityIncreasing
2022-09-15T16:48:16.961191image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)
ValueCountFrequency (%)
169359
100.0%
ValueCountFrequency (%)
169359
100.0%
ValueCountFrequency (%)
169359
100.0%

repeated_lat_long
Real number (ℝ≥0)

ZEROS

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.2273677533
Minimum0
Maximum1
Zeros53589
Zeros (%)77.3%
Negative0
Negative (%)0.0%
Memory size542.0 KiB
2022-09-15T16:48:16.989078image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum1
Range1
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.4191350509
Coefficient of variation (CV)1.843423462
Kurtosis-0.3074977856
Mean0.2273677533
Median Absolute Deviation (MAD)0
Skewness1.300965442
Sum15770
Variance0.1756741909
MonotonicityNot monotonic
2022-09-15T16:48:17.016325image/svg+xmlMatplotlib v3.5.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)
ValueCountFrequency (%)
053589
77.3%
115770
 
22.7%
ValueCountFrequency (%)
053589
77.3%
115770
 
22.7%
ValueCountFrequency (%)
115770
 
22.7%
053589
77.3%